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Data Science Course (Self Paced)

Learn Advanced Data Science & Machine Learning using Python

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Get Trained & Certified
for Data Science Jobs
in 2800 Companies

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Curriculum

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Hands-on Projects

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Industry Experts

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Live Class Hrs

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Assignments Hrs

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Course Fee

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Students

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Exclusive Offers!

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Interview Guarantee

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Download Brochure

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Enroll Now

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The Digital Vidya Advantage

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Get Certified by NASSCOM FutureSkills

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100% Interview Guarantee on Completion

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Curriculum approved for 2800 companies requirements

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box_shadow_horizontal_tablet=”0px” box_shadow_vertical_tablet=”0px” box_shadow_blur_tablet=”40px” box_shadow_spread_tablet=”0px” z_index_tablet=”500″]

Why Study Data Science?

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Huge Demand

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*AI Professionals employability gaps in Indian IT industry as per NASSCOM Report

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Great Salaries

[/et_pb_text][et_pb_image src=”https://www.digitalvidya.com/wp-content/uploads/2020/03/Data-Science-Salary-Range-per-Annum-1-1_f39dc9f5a7638e9e85e968b44aaab8b7.jpg” show_bottom_space=”off” _builder_version=”3.26.6″ width=”510px” width_phone=”100%” width_last_edited=”on|phone” height=”259px” height_last_edited=”on|desktop” /][et_pb_text _builder_version=”3.26.6″ text_font_size=”9px”]

*AI Professionals employability gaps in Indian IT industry as per NASSCOM Report

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Talk To Advisor

Discuss your Career Goals with Advisors

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Are you Ready to Learn Data Science?

[/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row column_structure=”1_2,1_2″ _builder_version=”3.25″ custom_padding=”0|0px|32px|0px|false|false”][et_pb_column type=”1_2″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text _builder_version=”3.26.6″]

Whether you are a student or an experienced professional, if you can fulfil following pre-requisites, you can be a Data Scientist

Pre-requisites

Programers or non-programmers with a desire to learn Programming
Good analytical skills
Passionate problem solver
Willing to spend 20 hrs/week for 3-4 months on training

[/et_pb_text][/et_pb_column][et_pb_column type=”1_2″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text _builder_version=”3.26.6″]

Profiles of Digital Vidya’s Students

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Enroll Now

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Discuss the course relevance for you

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NASSCOM FutureSkills Certified Course

[/et_pb_text][et_pb_text _builder_version=”3.26.6″ custom_margin=”-9px||0px||false|false”]

Get Trained & Certified for Data Science Jobs in 2800 Companies

[/et_pb_text][et_pb_text _builder_version=”3.18.7″ /][/et_pb_column][/et_pb_row][et_pb_row column_structure=”2_5,3_5″ _builder_version=”3.26.6″ custom_margin=”|auto||auto|false|false”][et_pb_column type=”2_5″ _builder_version=”3.26.6″][et_pb_image src=”https://www.digitalvidya.com/wp-content/uploads/2020/03/nasscom.png” align=”right” align_tablet=”center” align_last_edited=”on|desktop” _builder_version=”3.26.6″ width=”150px” height=”150px” custom_margin=”|40px|-70px||false|false” custom_padding=”||||false|false” z_index_tablet=”500″ box_shadow_horizontal_tablet=”0px” box_shadow_vertical_tablet=”0px” box_shadow_blur_tablet=”40px” box_shadow_spread_tablet=”0px” /][et_pb_image src=”https://www.digitalvidya.com/wp-content/uploads/2020/03/NASSCOM-Certificate-3_c1eed66c0483b13562be410d659999ea.jpg” url=”https://www.digitalvidya.com/wp-content/uploads/2020/03/NASSCOM-Certificate.jpg” url_new_window=”on” _builder_version=”3.26.6″ width=”238px” height=”326px” /][/et_pb_column][et_pb_column type=”3_5″ _builder_version=”3.26.6″][et_pb_text _builder_version=”3.26.6″ custom_padding=”0px|||||”]

NASSCOM FutureSkills has certified Digital Vidya’s Data Science Course as it covers 100% of the Data Science skills across Industries
NASSCOM Data Science curriculum is based on skills required by 2800+ NASSCOM member companies
Every course participant will get NASSCOM FutureSkills Certificate on successful course completion
20+ leading companies were involved in defining NASSCOM Course Curriculum

[/et_pb_text][et_pb_image src=”https://www.digitalvidya.com/wp-content/uploads/2020/03/nasscom-ai-expert.jpg” _builder_version=”3.26.6″ width=”600px” width_phone=”100%” width_last_edited=”on|desktop” height=”299px” height_last_edited=”on|desktop” /][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section bb_built=”1″ _builder_version=”3.26.6″ custom_padding=”1px|||||” prev_background_color=”#000000″ next_background_color=”#000000″][et_pb_row _builder_version=”3.25″ custom_padding=”0px|0px|0|0px|false|false” locked=”off”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text admin_label=”Talk To Advisor” _builder_version=”3.26.6″ text_text_shadow_horizontal_length=”text_text_shadow_style,%91object Object%93″ text_text_shadow_horizontal_length_tablet=”0px” text_text_shadow_vertical_length=”text_text_shadow_style,%91object Object%93″ text_text_shadow_vertical_length_tablet=”0px” 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Talk To Advisor

Discuss the course relevance for you

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50+ Placement Partners

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100% Interview Guarantee Offer

Digital Vidya offers 100% Interview Guaranteed support to eligible new graduates and working professionals, who get certified through Python for Data Science Course.

We have a dedicated placement cell, which works closely with our participants for their placement needs. Here is a snapshot of our placement process.

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On successful completion of the course including assignments & certifications, we work with the candidate to create an effective resume.

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The updated Resume is then shared with relevant organisations. On shortlisting, we follow-up with an initial round of discussion.

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Based on the organizations & the profiles for which the candidate is shortlisted, we help the candidate prepare for the complete interview process.

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After a successful interview, we guide the candidate from accepting the offer to joining the organization for a successful career.

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Enroll Now

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For further information on Placement Support on our Data Science Using Python Course

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Python Basic, Data Science, Data Visualization & Machine Learning using Python

Python for Data Science Course Syllabus

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Introduction to Data Science
Introduction to Python
Data Analysis Pipeline
What is Data Extraction
Types of Data
Raw and Processed Data
Data Wrangling
Overview of the Analytics Techniques
Analytics
Business Analytics
Business Intelligence
Industry Examples

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Fundamentals

Installation
Python – Syntax
Python – Variables and Datatypes
Python – Numbers
Strings
Sequences
List
Tuples
Ranges
Dictionary
Sets
Operators
If..Else.. Statements
For Loop
While Loop
Break
Continue
Pass
Date & Time
Functions
Packages and modules
Reading a File
Writing into File
Class & Objects
Python – Exceptions
Regular Exp
Mathematics

Functions in Python

class method vs static method in Python
Write an empty function in Python – pass statement
Yield instead of Return
Return Multiple Values
Partial Functions in Python
First Class functions in Python
Precision Handling
*args and **kwargs
Python closures
Function Decorators
Decorators in Python
Decorators with parameters in Python
Memoization using decorators in Python
Python bit functions on int (bit_length, to_bytes and from_bytes)

Object -Oriented Concepts

Class, Object and Members
Data Hiding and Object Printing
Inheritance, examples of an object, subclass and super
Polymorphism in Python
Class and static variable in Python
Class method and static method in Python
Changing class members
Constructors in Python
Destructors in Python
First-class function
str() vs repr()
str() vs vpr()
Metaprogramming with metaclasses
Class and instance attribute
Reflection
Barrier objects
Timer objects
Garbage collection

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Environment Setup
Database Connection
Creating a New Database
Creating Tables
Insert Operation
Read Operation
Update Operation
Join Operation
Performing Transactions

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ndarray
Array Creation
Data Type Objects
Data type Object (dtype) in NumPy
Indexing
Basic Slicing and ALinear Algebra
Sorting, Searching and Counting
Set 1 (Introduction)dvanced Indexing
Iterating Over Array
Binary Operations
Mathematical Function
String Operations
Set 2 (Advanced)
Multiplication of two Matrices in Single line using Numpy in Python

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Pandas DataFrame

Creating a Pandas DataFrame
Dealing with Rows and Columns in Pandas DataFrame
Indexing and Selecting Data with Pandas
Boolean Indexing in Pandas
Conversion Functions in Pandas DataFrame
Iterating over rows and columns in Pandas DataFrame
Working with Missing Data in Pandas
Working With Text Data
Working with Dates and Times
Merging, Joining and Concatenating

Data Analysis

Data visualization using Bokeh
Exploratory Data Analysis in Python
Data visualization with different Charts in Python
Data Analysis and Visualization with Python
Math operations for Data analysis

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Graphically Displaying Single Variable
Measures of Location
Measures of Spread
Displaying relationship – Bivariate Data
Scatterplot
Measures of association of two or more variables
Covariance and Correlation
Probability
Joint Probability and independent events
Conditional probability
Bayes’ Theorem
Prior, Likelihood and Posterior
Discrete Random Variable
Probability Distribution of Discrete Random Variable
Binomial Distribution
Continuous Random Variables
Probability Distribution Function
Uniform Distribution
Normal Distribution
Point Estimation
Interval Estimation
Hypothesis Testing
Testing a one-sided Hypothesis
Testing a two-sided Hypothesis

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Applications of Machine Learning
Supervised vs Unsupervised Learning
Python libraries suitable for Machine Learning

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Regression – Features and Labels
Regression – Training and Testing
Regression – Forecasting and Predicting
Regression – Theory and how it works
Regression – How to program the Best Fit Slope
Regression – How to program the Best Fit Line
Regression – R Squared and Coefficient of Determination Theory
Model evaluation methods

Classification

Classification Intro
Applying K Nearest Neighbors to Data
Euclidean Distance theory
Decision Trees
Regression Trees
Random Forests
Boosting Algorithm
Principal Component Analysis
Linear Discriminant Analysis

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Vector Basics
Support Vector Machine Fundamentals
Constraint Optimization with Support Vector Machine
Beginning SVM from Scratch in Python
Support Vector Machine Optimization in Python
Visualization and Predicting with our Custom SVM
Kernels Introduction
Soft Margin Support Vector Machine

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Handling Non-Numerical Data for Machine Learning
K-Means with Titanic Dataset
K-Means from Scratch in Python
Finishing K-Means from Scratch in Python
Hierarchical Clustering with Mean Shift Introduction
Introduction Naive Bayes Classifier
Naive Bayes Classifier with Scikit
Introduction into Text Classification using Naive Bayes
Python Implementation of Text Classification

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Content-based recommender systems
Collaborative Filtering

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Text Preprocessing
Noise Removal
Lexicon Normalization
Lemmatization
Stemming
Object Standardization
Text to Features (Feature Engineering on text data)
Syntactical Parsing
Dependency Grammar
Part of Speech Tagging
Entity Parsing
Phrase Detection
Named Entity Recognition
Topic Modelling
N-Grams
Statistical features
TF – IDF
Frequency / Density Features
Readability Features
Word Embeddings
Important tasks of NLP
Text Classification
Text Matching
Levenshtein Distance
Phonetic Matching
Flexible String Matching
Important NLP libraries

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Python Basics, Data Science, Data Visualisation & Machine Learning

Data Science Course Curriculum

[/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row _builder_version=”3.25″ custom_padding=”0|0px|27px|0px|false|false”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text admin_label=”Download curriculum (.pdf)” _builder_version=”3.26.6″ text_text_shadow_horizontal_length=”text_text_shadow_style,%91object Object%93″ text_text_shadow_horizontal_length_tablet=”0px” text_text_shadow_vertical_length=”text_text_shadow_style,%91object Object%93″ text_text_shadow_vertical_length_tablet=”0px” text_text_shadow_blur_strength=”text_text_shadow_style,%91object Object%93″ text_text_shadow_blur_strength_tablet=”1px” link_text_shadow_horizontal_length=”link_text_shadow_style,%91object Object%93″ link_text_shadow_horizontal_length_tablet=”0px” link_text_shadow_vertical_length=”link_text_shadow_style,%91object Object%93″ link_text_shadow_vertical_length_tablet=”0px” link_text_shadow_blur_strength=”link_text_shadow_style,%91object Object%93″ link_text_shadow_blur_strength_tablet=”1px” ul_text_shadow_horizontal_length=”ul_text_shadow_style,%91object Object%93″ ul_text_shadow_horizontal_length_tablet=”0px” ul_text_shadow_vertical_length=”ul_text_shadow_style,%91object Object%93″ ul_text_shadow_vertical_length_tablet=”0px” ul_text_shadow_blur_strength=”ul_text_shadow_style,%91object Object%93″ ul_text_shadow_blur_strength_tablet=”1px” ol_text_shadow_horizontal_length=”ol_text_shadow_style,%91object Object%93″ ol_text_shadow_horizontal_length_tablet=”0px” ol_text_shadow_vertical_length=”ol_text_shadow_style,%91object Object%93″ ol_text_shadow_vertical_length_tablet=”0px” ol_text_shadow_blur_strength=”ol_text_shadow_style,%91object Object%93″ ol_text_shadow_blur_strength_tablet=”1px” quote_text_shadow_horizontal_length=”quote_text_shadow_style,%91object Object%93″ quote_text_shadow_horizontal_length_tablet=”0px” quote_text_shadow_vertical_length=”quote_text_shadow_style,%91object Object%93″ quote_text_shadow_vertical_length_tablet=”0px” quote_text_shadow_blur_strength=”quote_text_shadow_style,%91object Object%93″ quote_text_shadow_blur_strength_tablet=”1px” header_text_shadow_horizontal_length=”header_text_shadow_style,%91object Object%93″ header_text_shadow_horizontal_length_tablet=”0px” header_text_shadow_vertical_length=”header_text_shadow_style,%91object Object%93″ header_text_shadow_vertical_length_tablet=”0px” header_text_shadow_blur_strength=”header_text_shadow_style,%91object Object%93″ header_text_shadow_blur_strength_tablet=”1px” header_2_text_shadow_horizontal_length=”header_2_text_shadow_style,%91object Object%93″ header_2_text_shadow_horizontal_length_tablet=”0px” header_2_text_shadow_vertical_length=”header_2_text_shadow_style,%91object Object%93″ header_2_text_shadow_vertical_length_tablet=”0px” header_2_text_shadow_blur_strength=”header_2_text_shadow_style,%91object Object%93″ header_2_text_shadow_blur_strength_tablet=”1px” header_3_text_shadow_horizontal_length=”header_3_text_shadow_style,%91object Object%93″ header_3_text_shadow_horizontal_length_tablet=”0px” header_3_text_shadow_vertical_length=”header_3_text_shadow_style,%91object Object%93″ header_3_text_shadow_vertical_length_tablet=”0px” header_3_text_shadow_blur_strength=”header_3_text_shadow_style,%91object Object%93″ header_3_text_shadow_blur_strength_tablet=”1px” header_4_text_shadow_horizontal_length=”header_4_text_shadow_style,%91object Object%93″ header_4_text_shadow_horizontal_length_tablet=”0px” header_4_text_shadow_vertical_length=”header_4_text_shadow_style,%91object Object%93″ header_4_text_shadow_vertical_length_tablet=”0px” header_4_text_shadow_blur_strength=”header_4_text_shadow_style,%91object Object%93″ header_4_text_shadow_blur_strength_tablet=”1px” header_5_text_shadow_horizontal_length=”header_5_text_shadow_style,%91object Object%93″ header_5_text_shadow_horizontal_length_tablet=”0px” header_5_text_shadow_vertical_length=”header_5_text_shadow_style,%91object Object%93″ header_5_text_shadow_vertical_length_tablet=”0px” header_5_text_shadow_blur_strength=”header_5_text_shadow_style,%91object Object%93″ header_5_text_shadow_blur_strength_tablet=”1px” header_6_text_shadow_horizontal_length=”header_6_text_shadow_style,%91object Object%93″ header_6_text_shadow_horizontal_length_tablet=”0px” header_6_text_shadow_vertical_length=”header_6_text_shadow_style,%91object Object%93″ header_6_text_shadow_vertical_length_tablet=”0px” header_6_text_shadow_blur_strength=”header_6_text_shadow_style,%91object Object%93″ header_6_text_shadow_blur_strength_tablet=”1px” box_shadow_horizontal_tablet=”0px” box_shadow_vertical_tablet=”0px” box_shadow_blur_tablet=”40px” box_shadow_spread_tablet=”0px” z_index_tablet=”500″ disabled_on=”on|on|on” disabled=”on”]

Download curriculum (.pdf)

[/et_pb_text][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section bb_built=”1″ module_id=”classes” _builder_version=”3.26.6″ custom_padding=”0|0px|0|0px|false|false” locked=”off” prev_background_color=”#000000″ next_background_color=”#000000″][et_pb_row _builder_version=”3.25″ custom_padding=”1px|0px|0|0px|false|false”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_divider _builder_version=”3.18.7″ /][/et_pb_column][/et_pb_row][et_pb_row _builder_version=”3.25″ custom_padding=”0|0px|0|0px|false|false” locked=”off”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text admin_label=”72+ Hours of Hands on Assignments” module_id=”assignments” _builder_version=”3.26.6″ text_font=”PT Sans|700|||||||” text_text_color=”#4daaf2″ text_font_size=”15px” locked=”off” text_text_shadow_horizontal_length=”text_text_shadow_style,%91object Object%93″ 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72+ Hours of Hands on Assignments

[/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row _builder_version=”3.25″ custom_padding=”0|0px|26.1719px|0px|false|false”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text admin_label=” Hands-on Python for Data Science Course Assignments” _builder_version=”3.26.6″ text_text_shadow_horizontal_length=”text_text_shadow_style,%91object Object%93″ text_text_shadow_horizontal_length_tablet=”0px” text_text_shadow_vertical_length=”text_text_shadow_style,%91object Object%93″ text_text_shadow_vertical_length_tablet=”0px” text_text_shadow_blur_strength=”text_text_shadow_style,%91object Object%93″ text_text_shadow_blur_strength_tablet=”1px” link_text_shadow_horizontal_length=”link_text_shadow_style,%91object Object%93″ link_text_shadow_horizontal_length_tablet=”0px” link_text_shadow_vertical_length=”link_text_shadow_style,%91object Object%93″ link_text_shadow_vertical_length_tablet=”0px” link_text_shadow_blur_strength=”link_text_shadow_style,%91object Object%93″ link_text_shadow_blur_strength_tablet=”1px” ul_text_shadow_horizontal_length=”ul_text_shadow_style,%91object Object%93″ ul_text_shadow_horizontal_length_tablet=”0px” ul_text_shadow_vertical_length=”ul_text_shadow_style,%91object Object%93″ ul_text_shadow_vertical_length_tablet=”0px” ul_text_shadow_blur_strength=”ul_text_shadow_style,%91object Object%93″ ul_text_shadow_blur_strength_tablet=”1px” ol_text_shadow_horizontal_length=”ol_text_shadow_style,%91object Object%93″ ol_text_shadow_horizontal_length_tablet=”0px” ol_text_shadow_vertical_length=”ol_text_shadow_style,%91object Object%93″ ol_text_shadow_vertical_length_tablet=”0px” ol_text_shadow_blur_strength=”ol_text_shadow_style,%91object Object%93″ ol_text_shadow_blur_strength_tablet=”1px” quote_text_shadow_horizontal_length=”quote_text_shadow_style,%91object Object%93″ quote_text_shadow_horizontal_length_tablet=”0px” quote_text_shadow_vertical_length=”quote_text_shadow_style,%91object Object%93″ quote_text_shadow_vertical_length_tablet=”0px” quote_text_shadow_blur_strength=”quote_text_shadow_style,%91object Object%93″ quote_text_shadow_blur_strength_tablet=”1px” header_text_shadow_horizontal_length=”header_text_shadow_style,%91object Object%93″ header_text_shadow_horizontal_length_tablet=”0px” header_text_shadow_vertical_length=”header_text_shadow_style,%91object Object%93″ header_text_shadow_vertical_length_tablet=”0px” header_text_shadow_blur_strength=”header_text_shadow_style,%91object Object%93″ header_text_shadow_blur_strength_tablet=”1px” header_2_text_shadow_horizontal_length=”header_2_text_shadow_style,%91object Object%93″ header_2_text_shadow_horizontal_length_tablet=”0px” header_2_text_shadow_vertical_length=”header_2_text_shadow_style,%91object Object%93″ header_2_text_shadow_vertical_length_tablet=”0px” header_2_text_shadow_blur_strength=”header_2_text_shadow_style,%91object Object%93″ header_2_text_shadow_blur_strength_tablet=”1px” header_3_text_shadow_horizontal_length=”header_3_text_shadow_style,%91object Object%93″ header_3_text_shadow_horizontal_length_tablet=”0px” header_3_text_shadow_vertical_length=”header_3_text_shadow_style,%91object Object%93″ header_3_text_shadow_vertical_length_tablet=”0px” header_3_text_shadow_blur_strength=”header_3_text_shadow_style,%91object Object%93″ header_3_text_shadow_blur_strength_tablet=”1px” header_4_text_shadow_horizontal_length=”header_4_text_shadow_style,%91object Object%93″ header_4_text_shadow_horizontal_length_tablet=”0px” header_4_text_shadow_vertical_length=”header_4_text_shadow_style,%91object Object%93″ header_4_text_shadow_vertical_length_tablet=”0px” header_4_text_shadow_blur_strength=”header_4_text_shadow_style,%91object Object%93″ header_4_text_shadow_blur_strength_tablet=”1px” header_5_text_shadow_horizontal_length=”header_5_text_shadow_style,%91object Object%93″ header_5_text_shadow_horizontal_length_tablet=”0px” header_5_text_shadow_vertical_length=”header_5_text_shadow_style,%91object Object%93″ header_5_text_shadow_vertical_length_tablet=”0px” header_5_text_shadow_blur_strength=”header_5_text_shadow_style,%91object Object%93″ header_5_text_shadow_blur_strength_tablet=”1px” header_6_text_shadow_horizontal_length=”header_6_text_shadow_style,%91object Object%93″ header_6_text_shadow_horizontal_length_tablet=”0px” header_6_text_shadow_vertical_length=”header_6_text_shadow_style,%91object Object%93″ header_6_text_shadow_vertical_length_tablet=”0px” header_6_text_shadow_blur_strength=”header_6_text_shadow_style,%91object Object%93″ header_6_text_shadow_blur_strength_tablet=”1px” box_shadow_horizontal_tablet=”0px” box_shadow_vertical_tablet=”0px” box_shadow_blur_tablet=”40px” box_shadow_spread_tablet=”0px” z_index_tablet=”500″]

Hands-on Python for Data Science Course Assignments

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Modules Assignments to strengthen Your Data Science Skills Using Python

Note: The following list is not comprehensive. We add/edit assignments based on feedback from both industry experts and participants.

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The variables, data types and all kinds of operators (arithmetic, logical, comparison) will be introduced in this assignment.

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The important data types of Python List, Dictionary etc will be covered in addition to conditional and iterative loops. Some aspects of data cleansing will also be covered.

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NumPy is an important Python library for numerical/statistical operations and is of utmost importance in Data Science. Here you will be introduced to the Numpy Library.

[/et_pb_accordion_item][et_pb_accordion_item title=”Data Manipulation using Pandas Library – I” _builder_version=”3.26.6″ open=”off”]

Data manipulation is critical to Data Science. This manipulation of data is done using Pandas library in Python. You will be introduced to Pandas, functions (iloc, tail, head, groupby, fillna, etc) which are most commonly used will be discussed here.

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This is the 2nd part of data manipulation using Pandas. You will be made to solve complex questions for manipulating data. You will build functions and apply those on the Pandas data frames which is practical and applicable.

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Time series is a kind of data which is often found for analysis. Analyzing, manipulating and making sense out of this data is an outcome of this assignment.

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Data visualization is an important part of Data Science. As we create stories/insights from the data, these stories/insights are shown through visualizations. This assignment will help to implement various visualizations using Matplotlib and Seaborn Python libraries.

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Data comes from disparate sources and it is a common use case to join/merge/concatenate multiple datasets into one. This assignment will help you learn to merge/concatenate datasets using Python and also make your work on melting/changing dimensions of datasets by converting rows to columns and vice versa

[/et_pb_accordion_item][et_pb_accordion_item title=”Statistics: Probability, Hypothesis Testing” _builder_version=”3.26.6″ open=”off”][/et_pb_accordion_item][et_pb_accordion_item title=”Multiple Linear Regression & Quadratic Regression Analysis” _builder_version=”3.26.6″ open=”off”][/et_pb_accordion_item][et_pb_accordion_item title=”Introduction to Trees, Decision Trees, Ensemble Learning (Random Forest)” _builder_version=”3.26.6″ open=”off”][/et_pb_accordion_item][et_pb_accordion_item title=”Classification Introduction, Logistics Regression & Text Analysis Using Classification Algorithms” _builder_version=”3.26.6″ open=”off”][/et_pb_accordion_item][et_pb_accordion_item title=”Unsupervised Learning, Unsupervised Learning Techniques-K Means Clustering, Hierarchical Clustering” _builder_version=”3.26.6″ open=”off”][/et_pb_accordion_item][et_pb_accordion_item title=”Bias-Variance Trade-off, Model Evaluation Techniques” _builder_version=”3.26.6″ open=”off”][/et_pb_accordion_item][et_pb_accordion_item title=”Logistic Regression Model Tuning” _builder_version=”3.26.6″ open=”off”][/et_pb_accordion_item][/et_pb_accordion][/et_pb_column][/et_pb_row][et_pb_row _builder_version=”3.25″ custom_padding=”1px|0px|0|0px|false|false”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text admin_label=”Download curriculum (.pdf)” _builder_version=”3.26.6″ custom_margin=”-30px||” z_index_tablet=”500″ text_text_shadow_horizontal_length_tablet=”0px” text_text_shadow_vertical_length_tablet=”0px” text_text_shadow_blur_strength_tablet=”1px” link_text_shadow_horizontal_length_tablet=”0px” link_text_shadow_vertical_length_tablet=”0px” link_text_shadow_blur_strength_tablet=”1px” ul_text_shadow_horizontal_length_tablet=”0px” ul_text_shadow_vertical_length_tablet=”0px” ul_text_shadow_blur_strength_tablet=”1px” ol_text_shadow_horizontal_length_tablet=”0px” ol_text_shadow_vertical_length_tablet=”0px” 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Download curriculum (.pdf)
Get complete details of this course

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4 Projects

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Python for Data Science Course Capstone Projects

Every participant is mandated to solve one Capstone Project to be eligible for our Python for Data Science Certification. The learner is encouraged to solve all available projects to sharpen the skills across several domains.

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Natural Language Processing

Duration: 3 Weeks

Project Description:

This is one of the most applied areas for AI, Data Science, and Machine Learning across domains and industries. The real world is filled with mostly messy text data, and handling text is an important step towards making smarter algorithms. Using IMDB dataset from the movie domain, the learner will apply the most common concepts of NLP.

Key Takeaway:

This project will empower the learners to build intermediate skills in the natural language processing domain. A few of the fundamentals of working with textual data covered in this project are:

Remove stop words
Apply Stemming and Lemmatization
Create a cluster of words
Build a sentiment analysis model and a clustering model

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Healthcare Analysis

Duration: 3 Weeks

Project Description:

Electroencephalography (EEG) is an electrophysiological monitoring method to record the electrical activity of the brain. For this project, we will use the large EEG database at UCI Machine learning repository. This data arises from a large study to examine EEG correlates of genetic predisposition to alcoholism. One fascinating question is whether the patterns are different for an alcoholic and regular subject?

Key Takeaway:

This capstone project focuses on EEG data analysis, giving an opportunity for students to learn through complexities in dealing with such complex real-world data. The project contains the following exercises:

Parse and store in an easily understandable and readable form
Exploratory data analysis to better understand the data
Using Statistical concepts like Hypothetical testing
Identify features to predict whether a subject is alcoholic or not
Use machine learning algorithms to develop a suitable classifier

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Bank Marketing

Duration: 3 Weeks

Project Description:

The banking industry is working in a very competitive environment and needs to strategize to grow its business. This project is related to the marketing campaigns related to term deposits, making an interesting multi-disciplinary work that mixes both the finance and the marketing domain.

Key Takeaway:

The approach to this project is to think, define, design, code, test and tune your solution, in such a way that you apply all aspects of the data science process. The data is a real-world data with unclean and null values.

The objective is to:

Build the model to predict if a customer will subscribe
Identify influential factors to form marketing strategies
Improve long-term relationship with the clients

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Deep Learning Based Project

Duration: 3 Weeks | Price: ₹5000 (Including Tax)

Project Description:

E-Commerce has experienced considerable growth since the dawn of the internet as a commercial enterprise. Deep Learning excels at identifying patterns in unstructured data and can predict the class of an uploaded image applied on eCommerce context. This project is an attempt to replicate virtual store assistance through image recognition over an eCommerce Fashion MNIST dataset.

Key Takeaway:

This project focuses on the implementation of Neural Networks to solve complex unstructured data problems. The objective is to:

Build the model to classify the various categories (analytic vertical) of clothing/fashion related images.
Understanding the implementation of deep learning concepts through Tensorflow and Keras.
Model optimization by tuning hyper-parameters and implementing dropout layers.

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Enroll Now

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For further information on Python for Data Science Capstone Projects

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Schedule of Data Science Course (Self Paced) With Python Online Training

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6 hours / week

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14 weeks

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72+ hours

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Saturday’s & Sunday’s

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Upcoming Data Science Course (Self Paced) Batch(es) start on

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5th july,2020 (Sat+Sun)

10 AM – 1:30 PM (IST)

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₹ 15,000

[/et_pb_blurb][/et_pb_column][/et_pb_row][et_pb_row module_id=”mod” _builder_version=”3.25″ custom_padding=”2px|0px|0|0px|false|false” locked=”off”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text _builder_version=”3.26.6″ custom_margin=”||-3px|||”]

Enroll Now

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Upcoming Data Science with Python Batches

6 hours / week

20 weeks

72+ hours

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+ Placement Support: Interview Guarantee

+ Eligibility: Open to all

+ Batch Date: NA

+ Timings: 3-6 PM | 6-9 PM

+ Weekday Batch: Tues – Fri

+ Price: [contentblock id=384 prod=”CN”]

Enroll Now

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+ Placement Support: Interview Guarantee

+ Eligibility: Open to all

+ Batch Date: 11 July 2020

+ Timings: 10 AM – 1:30 PM (IST)

+ Weekend Batch: Sat – Sun

+ Price: [contentblock id=384 prod=”CN”]

Enroll Now

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If you do not like the Python for Data Science training, take 100% refund within 15 days!

[/et_pb_text][et_pb_text _builder_version=”3.26.6″ custom_margin=”-10px||” /][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section bb_built=”1″ _builder_version=”3.22″ custom_padding=”0|0px|0|0px|false|false” prev_background_color=”#000000″ next_background_color=”#000000″][et_pb_row _builder_version=”3.25″ custom_padding=”0|0px|0|0px|false|false”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_divider _builder_version=”3.26.6″ /][/et_pb_column][/et_pb_row][et_pb_row _builder_version=”3.26.6″ custom_padding=”0|0px|10px|0px|false|false” disabled=”on” disabled_on=”on|on|on”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text _builder_version=”3.26.6″]

Qualifications for our Interview Guarantee Offer

BE/B.Tech Computer Science/IT/ MCA / MSc. IT / MA. Statistics / MA. Mathematics
CGPA of 6.0 & above (50% & above in MCA / MSc IT)
60% of Marks in 10th and 12th Exams
Immediately Available to Join the Organization
Successful Completion of the Course along with Aptitude & Coding Tests

Note: Students from Non-Metro/Non-IT cities need to be self-located in the hiring locations during the placment process.

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Langauge & Tools

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Data Science Programming Languages and Tools in this Course

You will become comfortable with Python Data Science tools that are widely used in the industry by Data Scientists.

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Python is becoming the first choice for Data Scientists. The learners will be learning to use all the relevant libraries, NumPy, Pandas, scikit-learn, Matplotlib.

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An open-source web application that contains live code, visualizations and narrative text. Learners will be using this for all their data science work.

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Download curriculum (.pdf)

Know everything that we teach in our Data Science with Python Course

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2 Certifications

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Data Science with Python Course Certifications

[/et_pb_text][et_pb_text _builder_version=”3.18.7″ /][/et_pb_column][/et_pb_row][et_pb_row column_structure=”1_2,1_2″ use_custom_gutter=”on” gutter_width=”2″ make_equal=”on” _builder_version=”3.25″ border_color_all=”#d55528″ custom_margin=”||10px”][et_pb_column type=”1_2″ _builder_version=”3.25″ use_background_color_gradient=”on” background_color_gradient_start=”#d55528″ background_color_gradient_end=”rgba(213,85,40,0)” background_color_gradient_start_position=”26%” background_color_gradient_end_position=”53%” custom_padding=”|||” custom_padding__hover=”|||”][et_pb_blurb title=”Data Science using Python Certificate” image=”https://www.digitalvidya.com/wp-content/uploads/2019/09/mohan_57f3154ad70acf157437fef7f9ed2aff-1-1_909cb71df6334e0beef21455ecf2c41b.jpg” image_max_width=”520%” _builder_version=”3.26.6″ header_font=”||||||||” header_font_size=”23px” body_font=”||||||||” border_width_all=”2px” border_color_all=”#d55528″ border_style_all=”double” text_orientation=”center” custom_padding=”10px||10px” custom_css_blurb_title=”font-size: 23px !important;”]

How to get this Certificate?

On successful completion of all assignments and 1 Capstone Project, the participant will get a Certificate issued by Digital Vidya.

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How to get this Certificate?

On successful passing of the Course, the participant will get a Certificate issued by NASSCOM FutureSkills

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Talk To Advisor

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For further information on Python Data Science Certifications

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100+ Hrs of Instructor-led Online Classes

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Why Learn Online?

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Online learning allows you to learn Python for Data Science with experts around the Globe.

Experience learning online yourself through a one-to-one Live Demo Session!

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Take A Demo Class

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We take 100s of demo sessions every day!

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Learn directly from Global experts with Experience from different industries and domains.

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You can attend live sessions from anywhere in the world including on Mobile.

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Save upto 120 hours of precious time, which would otherwise get wasted in travel.

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100+ hours of assignments ensure that you are learning hands-on.

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Even if you miss a live session, you can learn through the recording, which stays with you forever.

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Technology is dynamic. You will have access to the revised content for the lifetime.

[/et_pb_blurb][/et_pb_column_inner][/et_pb_row_inner][/et_pb_column][/et_pb_section][et_pb_section bb_built=”1″ module_id=”trainers” _builder_version=”3.22″ custom_padding=”0|0px|2px|0px|false|false” saved_tabs=”all” locked=”off” prev_background_color=”#000000″ next_background_color=”#000000″][et_pb_row _builder_version=”3.25″ custom_padding=”0|0px|0|0px|false|false” disabled_on=”on|on|on” disabled=”on”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_divider _builder_version=”3.18.7″ /][/et_pb_column][/et_pb_row][et_pb_row _builder_version=”3.25″ custom_padding=”0|0px|0|0px|false|false” link_option_url=”#trainers”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text module_id=”internships” _builder_version=”3.19.3″ text_font=”PT Sans|700|||||||” text_text_color=”#4daaf2″ text_font_size=”15px” text_line_height=”1em” header_font=”||||||||” locked=”off”]

Industry Experts as Trainers

[/et_pb_text][et_pb_text _builder_version=”3.26.6″]

Python for Data Science Course Trainers

Get trained by the Data Scientists with global experience and expertise across different industries.

[/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row _builder_version=”3.25″][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_code _builder_version=”3.26.6″][member-grid-course items=”Ganesh Naik,Rohit Kumar,Pritesh Shrivastava,Vaishali Garg,Nitika Malhotra,Rushabh Shah, Dilnoor Singh, Shaheer Ahmad Khan” perrow=”4″ linkprofiles=”1″ /][/et_pb_code][/et_pb_column][/et_pb_row][et_pb_row _builder_version=”3.25″ custom_padding=”0|0px|0|0px|false|false”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text admin_label=”Enroll Now” _builder_version=”3.26.6″ text_text_shadow_horizontal_length=”text_text_shadow_style,%91object Object%93″ text_text_shadow_horizontal_length_tablet=”0px” text_text_shadow_vertical_length=”text_text_shadow_style,%91object Object%93″ text_text_shadow_vertical_length_tablet=”0px” text_text_shadow_blur_strength=”text_text_shadow_style,%91object Object%93″ 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Enroll Now

100s of Students Attend our Data Science Using Python Demo Classes Every Week

[/et_pb_text][et_pb_divider _builder_version=”3.18.7″ /][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section bb_built=”1″ admin_label=”Testimonials” _builder_version=”3.22″ custom_padding=”1px|0px|0|0px|false|false” prev_background_color=”#000000″ next_background_color=”#000000″][et_pb_row _builder_version=”3.25″ custom_padding=”0|0px|26.1719px|0px|false|false”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text admin_label=”What do our Students say About us?” _builder_version=”3.26.6″ text_text_shadow_horizontal_length=”text_text_shadow_style,%91object Object%93″ text_text_shadow_horizontal_length_tablet=”0px” text_text_shadow_vertical_length=”text_text_shadow_style,%91object Object%93″ text_text_shadow_vertical_length_tablet=”0px” text_text_shadow_blur_strength=”text_text_shadow_style,%91object Object%93″ text_text_shadow_blur_strength_tablet=”1px” link_text_shadow_horizontal_length=”link_text_shadow_style,%91object Object%93″ link_text_shadow_horizontal_length_tablet=”0px” link_text_shadow_vertical_length=”link_text_shadow_style,%91object Object%93″ link_text_shadow_vertical_length_tablet=”0px” link_text_shadow_blur_strength=”link_text_shadow_style,%91object Object%93″ link_text_shadow_blur_strength_tablet=”1px” ul_text_shadow_horizontal_length=”ul_text_shadow_style,%91object Object%93″ ul_text_shadow_horizontal_length_tablet=”0px” ul_text_shadow_vertical_length=”ul_text_shadow_style,%91object Object%93″ ul_text_shadow_vertical_length_tablet=”0px” ul_text_shadow_blur_strength=”ul_text_shadow_style,%91object Object%93″ ul_text_shadow_blur_strength_tablet=”1px” ol_text_shadow_horizontal_length=”ol_text_shadow_style,%91object Object%93″ ol_text_shadow_horizontal_length_tablet=”0px” ol_text_shadow_vertical_length=”ol_text_shadow_style,%91object Object%93″ ol_text_shadow_vertical_length_tablet=”0px” ol_text_shadow_blur_strength=”ol_text_shadow_style,%91object Object%93″ ol_text_shadow_blur_strength_tablet=”1px” quote_text_shadow_horizontal_length=”quote_text_shadow_style,%91object Object%93″ quote_text_shadow_horizontal_length_tablet=”0px” quote_text_shadow_vertical_length=”quote_text_shadow_style,%91object Object%93″ quote_text_shadow_vertical_length_tablet=”0px” quote_text_shadow_blur_strength=”quote_text_shadow_style,%91object Object%93″ quote_text_shadow_blur_strength_tablet=”1px” header_text_shadow_horizontal_length=”header_text_shadow_style,%91object Object%93″ header_text_shadow_horizontal_length_tablet=”0px” header_text_shadow_vertical_length=”header_text_shadow_style,%91object Object%93″ header_text_shadow_vertical_length_tablet=”0px” header_text_shadow_blur_strength=”header_text_shadow_style,%91object Object%93″ header_text_shadow_blur_strength_tablet=”1px” header_2_text_shadow_horizontal_length=”header_2_text_shadow_style,%91object Object%93″ header_2_text_shadow_horizontal_length_tablet=”0px” header_2_text_shadow_vertical_length=”header_2_text_shadow_style,%91object Object%93″ header_2_text_shadow_vertical_length_tablet=”0px” header_2_text_shadow_blur_strength=”header_2_text_shadow_style,%91object Object%93″ header_2_text_shadow_blur_strength_tablet=”1px” header_3_text_shadow_horizontal_length=”header_3_text_shadow_style,%91object Object%93″ header_3_text_shadow_horizontal_length_tablet=”0px” header_3_text_shadow_vertical_length=”header_3_text_shadow_style,%91object Object%93″ header_3_text_shadow_vertical_length_tablet=”0px” header_3_text_shadow_blur_strength=”header_3_text_shadow_style,%91object Object%93″ header_3_text_shadow_blur_strength_tablet=”1px” header_4_text_shadow_horizontal_length=”header_4_text_shadow_style,%91object Object%93″ header_4_text_shadow_horizontal_length_tablet=”0px” header_4_text_shadow_vertical_length=”header_4_text_shadow_style,%91object Object%93″ header_4_text_shadow_vertical_length_tablet=”0px” header_4_text_shadow_blur_strength=”header_4_text_shadow_style,%91object Object%93″ header_4_text_shadow_blur_strength_tablet=”1px” header_5_text_shadow_horizontal_length=”header_5_text_shadow_style,%91object Object%93″ header_5_text_shadow_horizontal_length_tablet=”0px” header_5_text_shadow_vertical_length=”header_5_text_shadow_style,%91object Object%93″ header_5_text_shadow_vertical_length_tablet=”0px” header_5_text_shadow_blur_strength=”header_5_text_shadow_style,%91object Object%93″ header_5_text_shadow_blur_strength_tablet=”1px” header_6_text_shadow_horizontal_length=”header_6_text_shadow_style,%91object Object%93″ header_6_text_shadow_horizontal_length_tablet=”0px” header_6_text_shadow_vertical_length=”header_6_text_shadow_style,%91object Object%93″ header_6_text_shadow_vertical_length_tablet=”0px” header_6_text_shadow_blur_strength=”header_6_text_shadow_style,%91object Object%93″ header_6_text_shadow_blur_strength_tablet=”1px” box_shadow_horizontal_tablet=”0px” box_shadow_vertical_tablet=”0px” box_shadow_blur_tablet=”40px” box_shadow_spread_tablet=”0px” z_index_tablet=”500″]

What do our Students say About us?

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It was a tremendous journey right from the beginning. Huge opportunity opened in front of us in Data Science world.

[/et_pb_testimonial][et_pb_testimonial author=”Prerna Sathiyal” job_title=”Student” portrait_url=”https://www.digitalvidya.com/wp-content/uploads/2019/01/3_cbb80b195b507c6eb15f056b1103ae1a.jpg” quote_icon=”off” quote_icon_color=”#15314E” quote_icon_background_color=”#ffffff” portrait_width=”100px” portrait_height=”100px” _builder_version=”3.26.6″ body_font=”Open Sans||||||||” body_font_size=”16px” body_line_height=”2em” background_color=”#ffffff” border_width_all=”1px” border_color_all=”rgba(21,49,78,0.2)” border_radii_portrait=”on|100px|100px|100px|100px” border_width_all_portrait=”3px” border_color_all_portrait=”#d55528″ box_shadow_style_image=”preset1″ custom_padding=”||60px||false|false” animation_style=”fold” animation_delay=”400ms” locked=”off”]

Great experience. Easy and organized learning, great approach.

[/et_pb_testimonial][/et_pb_column][et_pb_column type=”1_3″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_testimonial author=”Rahul God” job_title=”Founder COO” portrait_url=”https://www.digitalvidya.com/wp-content/uploads/2019/01/2_78da23a792022b70eba3d4f817f35b00.jpg” quote_icon=”off” quote_icon_color=”#15314E” quote_icon_background_color=”#ffffff” portrait_width=”100px” portrait_height=”100px” _builder_version=”3.26.6″ body_font=”Open Sans||||||||” body_font_size=”16px” body_line_height=”2em” background_color=”#ffffff” border_width_all=”1px” border_color_all=”rgba(21,49,78,0.2)” border_radii_portrait=”on|100px|100px|100px|100px” border_width_all_portrait=”3px” border_color_all_portrait=”#d55528″ box_shadow_style_image=”preset1″ custom_padding=”||60px||false|false” animation_style=”fold” animation_delay=”400ms” locked=”off”]

Digital Vidya gave me a comprehensive knowledge of Data science within a very short period of time.

[/et_pb_testimonial][et_pb_testimonial author=”Arvind S” job_title=”Academician” portrait_url=”https://www.digitalvidya.com/wp-content/uploads/2019/01/5_52db069967f53fbfd65e397b8344d650.jpg” quote_icon=”off” quote_icon_color=”#ffffff” quote_icon_background_color=”#15314E” portrait_width=”100px” portrait_height=”100px” _builder_version=”3.19.4″ body_font=”Open Sans||||||||” body_font_size=”16px” body_line_height=”2em” background_color=”#2F3B5F” border_radii_portrait=”on|100px|100px|100px|100px” border_width_all_portrait=”3px” border_color_all_portrait=”#ffffff” box_shadow_style_image=”preset1″ background_layout=”dark” animation_style=”fold” animation_delay=”150ms”]

Case studies and projects improved my skills and given me confidence to call myself a data scientist.

[/et_pb_testimonial][/et_pb_column][et_pb_column type=”1_3″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_testimonial author=”Anshul Singh” company_name=”Student” portrait_url=”https://www.digitalvidya.com/wp-content/uploads/2019/01/6_4da5384cd29e15bdd34b6f7ac8ab4dfc.jpg” quote_icon=”off” quote_icon_color=”#15314e” quote_icon_background_color=”#ffffff” portrait_width=”100px” portrait_height=”100px” _builder_version=”3.26.6″ body_font=”Open Sans||||||||” body_font_size=”16px” body_line_height=”2em” background_color=”#f1f1f1″ border_radii_portrait=”on|100px|100px|100px|100px” border_width_all_portrait=”3px” box_shadow_style_image=”preset1″ custom_padding=”||60px||false|false” animation_style=”fold” animation_delay=”200ms”]

This course is best for beginners and it will give you complete exposure of every field of Data Science and Machine Learning.

[/et_pb_testimonial][et_pb_testimonial author=”Lipi Sahu” job_title=”Student” portrait_url=”https://www.digitalvidya.com/wp-content/uploads/2019/01/4_c117dfb9b46b80063da8c3661d9d8442.jpg” quote_icon=”off” quote_icon_color=”#ffffff” quote_icon_background_color=”#ffa727″ portrait_width=”100px” portrait_height=”100px” _builder_version=”3.26.6″ body_font=”Open Sans||||||||” body_font_size=”16px” body_line_height=”2em” background_color=”#d55528″ border_radii_portrait=”on|100px|100px|100px|100px” border_width_all_portrait=”3px” border_color_all_portrait=”#ffffff” box_shadow_style_image=”preset1″ background_layout=”dark” custom_padding=”||64px||false|false” animation_style=”fold” locked=”off” inline_fonts=”Montserrat”]

It was a great experience. Got to learn many new things going on in the present industry.

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What do the Industry Leaders say About us?

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Data Science with Python Course FAQs

General

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The Python Data Science course is thoughtfully designed to allow learners with programming background to make a
transition into the analytics industry with the correct skill-sets.

We recommend this course to the following:

Students BE/BTech/MCS/MCA who aspire to make a career into the growing field of Data Science/AI
Software professionals who aspire to explore a career in the field of Data Science
IT professionals with a passion for Statistics, Problem-solving, Machine Learning
Analytics professionals who want to solve deep problems using a programming language

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You will be getting access to the recording of every class for your own revision and practice. In case you miss a class, it is important that you go through the topics using the recording prior to the next class, so that you can follow through the next session effectively. Also, you will be required to submit the assignment on time even for the missed class.

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This is a comprehensive course that will help you gain an in-depth understanding of end to end data science. You’ll build the foundation of statistics, SQL, Exploratory Data Science, Machine Learning, Visualisation using both Python and Tableau. You will also have the option of learning R whenever you come across a project that is using R in your career.

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Digital Vidya offers 100% Interview Guaranteed support to eligible new graduates and working professionals, who get certified through Python for Data Science Course.

[/et_pb_toggle][/et_pb_column][/et_pb_row][et_pb_row _builder_version=”3.25″ custom_padding=”27px|0px|0|0px|false|false”][et_pb_column type=”4_4″ _builder_version=”3.25″ custom_padding=”|||” custom_padding__hover=”|||”][et_pb_text admin_label=”BE/B Tech/MCA/MCS Students/Fresh Graduates ” _builder_version=”3.26.6″ text_text_shadow_horizontal_length=”text_text_shadow_style,%91object Object%93″ text_text_shadow_horizontal_length_tablet=”0px” text_text_shadow_vertical_length=”text_text_shadow_style,%91object Object%93″ text_text_shadow_vertical_length_tablet=”0px” text_text_shadow_blur_strength=”text_text_shadow_style,%91object Object%93″ text_text_shadow_blur_strength_tablet=”1px” link_text_shadow_horizontal_length=”link_text_shadow_style,%91object Object%93″ link_text_shadow_horizontal_length_tablet=”0px” link_text_shadow_vertical_length=”link_text_shadow_style,%91object Object%93″ link_text_shadow_vertical_length_tablet=”0px” link_text_shadow_blur_strength=”link_text_shadow_style,%91object Object%93″ link_text_shadow_blur_strength_tablet=”1px” ul_text_shadow_horizontal_length=”ul_text_shadow_style,%91object Object%93″ ul_text_shadow_horizontal_length_tablet=”0px” ul_text_shadow_vertical_length=”ul_text_shadow_style,%91object Object%93″ ul_text_shadow_vertical_length_tablet=”0px” ul_text_shadow_blur_strength=”ul_text_shadow_style,%91object Object%93″ ul_text_shadow_blur_strength_tablet=”1px” ol_text_shadow_horizontal_length=”ol_text_shadow_style,%91object Object%93″ ol_text_shadow_horizontal_length_tablet=”0px” ol_text_shadow_vertical_length=”ol_text_shadow_style,%91object Object%93″ ol_text_shadow_vertical_length_tablet=”0px” ol_text_shadow_blur_strength=”ol_text_shadow_style,%91object Object%93″ ol_text_shadow_blur_strength_tablet=”1px” quote_text_shadow_horizontal_length=”quote_text_shadow_style,%91object Object%93″ quote_text_shadow_horizontal_length_tablet=”0px” quote_text_shadow_vertical_length=”quote_text_shadow_style,%91object Object%93″ quote_text_shadow_vertical_length_tablet=”0px” quote_text_shadow_blur_strength=”quote_text_shadow_style,%91object Object%93″ quote_text_shadow_blur_strength_tablet=”1px” header_text_shadow_horizontal_length=”header_text_shadow_style,%91object Object%93″ header_text_shadow_horizontal_length_tablet=”0px” header_text_shadow_vertical_length=”header_text_shadow_style,%91object Object%93″ header_text_shadow_vertical_length_tablet=”0px” header_text_shadow_blur_strength=”header_text_shadow_style,%91object Object%93″ header_text_shadow_blur_strength_tablet=”1px” header_2_text_shadow_horizontal_length=”header_2_text_shadow_style,%91object Object%93″ header_2_text_shadow_horizontal_length_tablet=”0px” header_2_text_shadow_vertical_length=”header_2_text_shadow_style,%91object Object%93″ header_2_text_shadow_vertical_length_tablet=”0px” header_2_text_shadow_blur_strength=”header_2_text_shadow_style,%91object Object%93″ header_2_text_shadow_blur_strength_tablet=”1px” header_3_text_shadow_horizontal_length=”header_3_text_shadow_style,%91object Object%93″ header_3_text_shadow_horizontal_length_tablet=”0px” header_3_text_shadow_vertical_length=”header_3_text_shadow_style,%91object Object%93″ header_3_text_shadow_vertical_length_tablet=”0px” header_3_text_shadow_blur_strength=”header_3_text_shadow_style,%91object Object%93″ header_3_text_shadow_blur_strength_tablet=”1px” header_4_text_shadow_horizontal_length=”header_4_text_shadow_style,%91object Object%93″ header_4_text_shadow_horizontal_length_tablet=”0px” header_4_text_shadow_vertical_length=”header_4_text_shadow_style,%91object Object%93″ header_4_text_shadow_vertical_length_tablet=”0px” header_4_text_shadow_blur_strength=”header_4_text_shadow_style,%91object Object%93″ header_4_text_shadow_blur_strength_tablet=”1px” header_5_text_shadow_horizontal_length=”header_5_text_shadow_style,%91object Object%93″ header_5_text_shadow_horizontal_length_tablet=”0px” header_5_text_shadow_vertical_length=”header_5_text_shadow_style,%91object Object%93″ header_5_text_shadow_vertical_length_tablet=”0px” header_5_text_shadow_blur_strength=”header_5_text_shadow_style,%91object Object%93″ header_5_text_shadow_blur_strength_tablet=”1px” header_6_text_shadow_horizontal_length=”header_6_text_shadow_style,%91object Object%93″ header_6_text_shadow_horizontal_length_tablet=”0px” header_6_text_shadow_vertical_length=”header_6_text_shadow_style,%91object Object%93″ header_6_text_shadow_vertical_length_tablet=”0px” header_6_text_shadow_blur_strength=”header_6_text_shadow_style,%91object Object%93″ header_6_text_shadow_blur_strength_tablet=”1px” box_shadow_horizontal_tablet=”0px” box_shadow_vertical_tablet=”0px” box_shadow_blur_tablet=”40px” box_shadow_spread_tablet=”0px” z_index_tablet=”500″]

BE/B Tech/MCA/MCS Students/Fresh Graduates

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Salaries offered to the freshers vary depending upon factors like premium institutes on-campus versus off-campus. Also, many companies take in interns at and then offer them employment based on performance. Later is most prevalent for off-campus hiring.

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Start-up companies are more flexible to hire freshers as they are in the growth phase and they are your optimal chance to get an immediate job and make an entry in the new field. The best part of working with startups is that you will have the opportunity to be the big fish, contributing in building core pieces the work. You should always grab the first job that you get in the new field, gain valuable experience in the first company. The key factor is how much can you learn and contribute in your early years, rather than the size of the company, big or small.

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Once you refuse the offer, you may have to wait your turn for the next opportunity. We will not promise you the next interview.

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You are taken as a trainee – Junior Data Analyst, Data Scientist. You may get a different role and technology based on the requirements and your performance in the selection process.

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The more flexible you are, you increase your chances of getting started with your career.

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You will not be eligible for any refund in case of non-completion of the course.

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Not sure, what to learn and how it will help you?

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Talk To Advisor

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Not sure about online classes?

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Take A Demo Class

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Check the available dates

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Enroll Now

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Data Science Course (Self Paced)

Learn Advanced Data Science & Machine Learning using Python

Students

The Digital Vidya Advantage

Get Certified by NASSCOM FutureSkills

100% Interview Guarantee on Completion

Curriculum approved for 2800 companies requirements

Why Study Data Science?

Huge Demand

Great Salaries

Are you Ready to Learn Data Science?

Profiles of Digital Vidya’s Students

Get Trained & Certified for Data Science Jobs in 2800 Companies

100% Interview Guarantee Offer

Python for Data Science Course Syllabus

Data Science Course Curriculum

Hands-on Python for Data Science Course Assignments

Modules Assignments to strengthen Your Data Science Skills Using Python

Python for Data Science Course Capstone Projects

Natural Language Processing

Duration: 3 Weeks

Healthcare Analysis

Duration: 3 Weeks

Bank Marketing

Duration: 3 Weeks

Deep Learning Based Project

Duration: 3 Weeks | Price: ₹5000 (Including Tax)

Schedule of Data Science Course (Self Paced) With Python Online Training

5th july,2020 (Sat+Sun)

Upcoming Data Science with Python Batches

Qualifications for our Interview Guarantee Offer

Data Science Programming Languages and Tools in this Course

Data Science with Python Course Certifications

Why Learn Online?

Python for Data Science Course Trainers

Get trained by the Data Scientists with global experience and expertise across different industries.

What do our Students say About us?

What do the Industry Leaders say About us?

Data Science with Python Course FAQs

General

BE/B Tech/MCA/MCS Students/Fresh Graduates

Discuss With A Career Advisor