Machine Learning Course

Advanced Course to Learn Machine Learning

Landscape of Machine Learning

  • 2.3 Million Machine Learning Jobs will be created by 2020
  • Average Salary Base for Machine Learning Jobs is $146,085
  • 10,000+ Monthly Machine Learning Job Openings
  • Initial Salary 5,00,000 – 12,00,000 INR Per Annum
  • Machine Learning Engineers Rule The Top 10 AI Jobs List


In-Depth Advanced Modules 


Hands-on Projects


Career Mentoring 


Hours of Live Classes


Placement Partners




Exclusive Offers!


Certification Validity 


Job Assistance

Know more about our Machine Learning Course

The Journey of a Data Scientist

Why Should You Take this Machine Learning Course?

Machine Learning is one of the hottest career choices today. It is one of the fastest-growing tech employment areas with jobs created far outnumbering the talent pool available.

According to Gartner, 2.3 million Machine Learning Jobs will be generated by 2020. Indeed job trends report also reveals that in terms of most in-demand, AI jobs, Machine Learning Engineer tops the chart with 29.10% increase in job postings.

Today, every industry is going gaga after Artificial Intelligence. This makes it ideal to take up a Machine Learning Course.

By bringing better career opportunities, Online Machine Learning Courses have become the shining star of the moment. 

Who is this Course For?

– People with knowledge of Python Programming
– Candidates with an understanding of Statistics, Algebra & Calculus

Our Machine Learning Online Course Enrollments Map

  • Students 40% 40%
  • IT Professionals 60% 60%

13 Modules

Machine Learning Online Course Curriculum Details

  • 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
  • Applications of Machine Learning
  • Supervised vs Unsupervised Learning
  • Python libraries suitable for Machine Learning
  • 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 Intro
  • Applying K Nearest Neighbors to Data
  • Euclidean Distance theory
  • Decision Trees
  • Regression Trees
  • Random Forests
  • Boosting Algorithm
  • Principal Component Analysis
  • Linear Discriminant Analysis
  • 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
  • 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
  • Content-based recommender systems
  • Collaborative Filtering
  • 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
Learn more about our Machine Learning Course Curriculum

15+ Hrs of Hands-on Assignments

Hands-on Machine Learning Course Assignments 

Well researched assignments have the potential to take the participants on an exciting journey to execute their learnings. That’s our mantra at Digital Vidya.

Each assignment of Digital Vidya’s Machine Learning Course is designed with a focus to provide the best practical experience. Our module assignments to learn Machine Learning focus on enhancing the confidence of our participants.

Our Assignments are close to the actual occurrences in the industry out there. These assignments will be a propeller to helping you learn Machine Learning practically. 

Statistics: Probability, Hypothesis Testing
Multiple Linear Regression & Quadratic Regression Analysis
Introduction to Trees, Decision Trees, Ensemble Learning (Random Forest)
Classification Introduction, Logistics Regression & Text Analysis Using Classification Algorithms
Unsupervised Learning, Unsupervised Learning Techniques-K Means Clustering, Hierarchical Clustering
Bias-Variance Trade-off, Model Evaluation Techniques
Logistic Regression Model Tuning
Know the complete offering of our Machine Learning Course

Capstone Projects on Offer

Best in Class Capstone Projects to Learn Machine Learning

To learn Machine learning in the best possible and hands-on method, Digital Vidya’s Machine Learning Course comes with best in class capstone Projects. At the end of each batch, we hold a Capstone Project competition that is open for our students. Successful participants win prizes and recommendations from their lead trainers.

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:

  1. Remove stop words
  2. Apply Stemming and Lemmatization
  3. Create a cluster of words
  4. Build a sentiment analysis model and a clustering model

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:

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

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:

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

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:

  1. Build the model to classify the various categories (analytic vertical) of clothing/fashion related images.
  2. Understanding the implementation of deep learning concepts through Tensorflow and Keras.
  3. Model optimization by tuning hyper-parameters and implementing dropout layers.
Get more details about the Capstone Projects of this Machine Learning Course

Machine Learning Course Schedule

Online Live Machine Learning Classes

39+ Hours of in-depth live sessions


Duration of Our Machine Learning Training

13 Weeks


Machine Learning Course Assignments

25+ Hours


Python Programming, Statistics, Calculus, & Algebra


Upcoming batches of Python Machine Learning Online Training



8 Dec, 2019 (Sunday)

10 AM -1:30 PM (IST)

Know the complete offering of our Machine Learning Course

2 Tools

Machine Learning Tools You’ll Learn

You will master Python and Jupyter Notebooks by the end of this course.

Language: Python

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.

Tool: Jupyter Notebook

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

Machine Learning Training Schedule

Why Learn Machine Learning Online?

Digital Vidya has a legacy of 9+ years in which we have trained 35,000+ Professionals from 55+ Countries of the World. 

We counsel 100s of candidates every day : )

Global Trainers

Learn directly from expert Machine Learning Trainers recognised for their expertise Globally.

Attend from Anywhere

Enjoy the power of mobility and learn while you are on the move. 

No Need to Travel

Save time that would otherwise be wasted in commuting. 

Interactive & Practical

15+ hours of assignments ensure that you learn hands-on.

No Time Constraints

Say bye-bye to time constraints. Revise at your own pace. 

Lifetime Updates

Get access to revised content for your entire life. 

Industry Expert as Your Machine Learning Trainer

Top Machine Learning Trainers Known Across the Industry

Get trained by world-renowned Machine Learning Trainers! All our Online Machine Learning Course trainers have 10+ years of industry experience. Btw, in case you don’t like the training, you can opt out within 3 days and request a full refund.

Get Complete Details of Digital Vidya’s Machine Learning Course

Industry Expert as Your Machine Learning Course Advisor

Our Machine Learning Course Advisers

Get Complete Details of Digital Vidya’s Machine Learning Course

50+ Placement Partners

100% Interview Guarantee Offer

Digital Vidya offers a 100% Interview Guarantee for its Online Machine Learning 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.

Resume Creation

On successful completion of the course, which includes submission of assignments & attaining necessary certifications, we work with the candidates to create an effective resume.


Job Application

The updated resume is shared with relevant organisations and agencies including our partners. On shortlisting, we help the candidate to pass the initial round of discussion.


Interview Readiness

Based on the organizations needs & candidates ability, we train them to maneuver themselves to crack the interview. This stage helps the candidate to be 100% ready.


Selection & Joining

After a successful interview, we guide the candidate from accepting the offer to joining the organization for a successful career. We help him to stand out at his workplace.


For further information on Placement Support

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 placement process.

2 Certifications

Machine Learning Certifications

Digital Vidya's Machine Learning Certification

How to get this Certificate?

On successful completion of all assignments and the project, the participant will get a Machine Learning Certificate issued by Digital Vidya. He has to have a minimum 80% attendance too.

Vskills Machine Learning Certification

How to get this Certificate?

On successful passing of the Vskills examination, the participant will get a Machine Learning Certificate issued by Vskills. (A nominal examination fee involved) 

For further information on Machine Learning Certifications

Our Machine Learning Course Student Reviews

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

Mohan Kumar

Senior Software Engineer

Great experience. Easy and organized learning, great approach.

Prerna Sathiyal


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

Rahul God

Founder COO

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

Arvind S


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

Anshul Singh


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

Lipi Sahu


Reviews of Expert Industry Leaders

Digital Vidya is doing a great job at bringing data analytics to the rest of the world!

Akshay Sehgal, General Manager

Digital Vidya is doing a great job of bringing people from diverse set of experiences to one platform for creating the best of Data Science skill pipeline.

Ambuj Kathuria, Head – Data & Analytics

Creating a talent pool in India with Practical hands-on experience in Analytics and Data Science is the need of the hour. Platforms like Digital Vidya are critical to filling this gap.

Ravi Vijayaraghavan, President and Head – Analytics and Decision Sciences

Machine Learning Course FAQs

Who can do a Machine Learning Course?

The Machine Learning Online Course is perfect for people who want to build their career in the Artificial Intelligence industry. We recommend this course to students BE/BTech/MCS/MCA, software professionals, IT professionals, Data Professionals and engineers.

What is the Salary of a Machine Learning Engineer?

Your salary will completely depend on your skills. Machine Learning jobs for freshers may vary between ₹ 699,807- 891,326. With a good knowledge of data analysis, algorithms and a few years of experience, you may expect a salary of ₹ 1,759,777 monthly or ₹ 9, 00,000 per annum.

How long is the Machine Learning Course?

This Machine Learning Course will take between 3-4 months to complete. The instructor-led sessions are of 50+ hrs. You will also have to work on assignments and case studies.

What job opportunities will I get after completing the Machine Learning Course?

After successful completion of the Machine Learning Course, you will get opportunities of being a Business Analyst, Product Analyst, Machine Learning Engineer or a Data Scientist.


Discuss with a Career Advisor

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