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How to Choose the Right Data Science/Analytics/Big Data Training?

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It was just another day. I was browsing the Internet, checking out attractive offers on Data Science courses. The online marketplace is flooded with thousands of Data Science courses to choose from. Most training academies offer attractive discounts on Data Science, Analytics, and Big Data courses. Some offer courses that develop your mathematical and statistical skills for an entry into Data Science career. Some others have a module that hones your programming skills for data analysis and predictive analysis.

You may buy one course to get another one for free. However, it takes more than just online sales carnivals or pretty packages to choose the right Data Science/Analytics/Big Data training for yourself.

Picking the premier institutes that offer the best Data Science courses, requires a basic understanding of the course, individual offerings (so that you can compare courses and make the best choice), personal career plans, and much more. In this discussion, I will offer a few guidelines for choosing the best Data Science training for yourself. I will also help you choose from some of the best Data Science courses available.

Who can be a Data Scientist?

You can be. I can be. Anyone of us can be a Data Science pro, if we are passionate about Data Science, and want to hone our data mining and statistical modeling skills, and are eager to know more about data preparation. The willingness to learn about Data Science presentation skills, and putting it into work, is all that matters. You may have a programming background, a computer science background, a purely mathematics/statistics background or even non-programming background, there is a tool for you there.

You may do wonders in Data Science if you choose the right Data Science course. Here I have pulled out information from some of the best-known Data Science training academies. They have courses for beginners, certification courses for advanced learners, and also in-house projects to work upon. Coming from a different academic background has its advantages. You may choose a Data Science training that sharpens your skills, and also prepares you better as a Data Science professional.

Choosing the Best Data Science/Analytics/Big Data Training

Choosing the Best Data Science Courses

Most Data Science or Big Data courses offer comprehensive modules that teach you how to clean and prepare your data for analysis, how to perform basic visualization of your data, how to model your data and curve-fit your data. Choose your course depending upon your academic background and career plans.

Best Data Science Courses for Freshers

If you are a beginner without a programming background but want to become a data scientist, go for a certification course that teaches you statistics, machine learning, R and SAS programming from the scratch. You will also learn about data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R language. The best Data Science courses for newbies allow them to get hands-on practice on R CloudLab by implementing various real-life, industry-based projects. I suggest you work on 6 projects if working 4 is a mandatory requirement for certification because the additional practical experience will add to your confidence. However, mind you, just master one tool, do not learn them all. Companies want solutions to their problems not your familiarity with different tools.

Best Data Science Courses for Python Professionals

Students with a background in Python programming are always willing to take up Data Science as a career option. Being a Python programmer, you should look for a Data Science course that covers areas like plotting, stochastic programs, probability and statistics, random walks, Monte Carlo simulations, modeling data, optimization problems, and clustering. If you are an experienced Python programmer, go for an advanced course in relational databases, Map Reduce and No-SQL. To choose the best Data Science training programs, you should have a basic understanding of Python programming concepts. You may learn more from code academy, learn basic statistics, and the fundamentals of machine learning before you sign up for a course in Data Science.

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Best Data Science Courses for Statistics and Mathematics Students

If you have a Statistics and programming background, you should go for an advanced course in Data Science, that covers concepts like machine learning, visualization, data mining, programming, and data munging. You will also learn about the popular scientific Python libraries such as Numpy, Scipy, Scikit-learn, and Pandas. While comparing course offerings, go for a Data Science course that stresses upon machine learning concepts such as PCA (dimensionality reduction), k-means and logistic regression. You will need to put in extra efforts for solving problems and exercises to become an expert in Data Science.

Students with a strong mathematics background can opt for a Data Science course that covers Robotics in details. It also gives them a hands-on experience with statistical modeling techniques. Best Data Science courses include real-world examples of how analytics is used to significantly improve a business. Make sure that the Data Science training contains a good number of the lectures and ample problem sets for practice. The best Data Science training in the industry includes plenty of problems and practice projects for students to gain confidence.

Best Data Science Courses for Experienced Database Professionals

If you are a database guy and want to be data scientist sometime in near future, the best Data Science courses for you should include fundamental algorithms and techniques to deal with Big Data. You need to gain a thorough knowledge of concepts like MapReduce, Locality Sensitive Hashing, Page Rank, and algorithms for Large Graphs and Data Streams. Make sure that course includes important practical applications, such as Web Search, Recommender Systems, and Online Advertising. Being an experienced database programmer, you should give special importance to dimensionality reduction.

Choosing the Best Big Data Courses for Success

Take a deep dive into Big Data. Take up a Big Data course that teaches you the basics of using Hadoop with MapReduce, Spark, Pig, and Hive. Most of the beginner courses for Big Data explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and how each impacts data collection, monitoring, storage, analysis, and reporting. You also learn to identify Big Data problems and should be able to recast Big Data problems as Data Science questions. Once you are through the fundamentals of Big Data landscape, you should be able to perform predictive modeling and leverage graph analytics to model problems.

If you have already worked on Big Data projects for a while, then I would advise you to go for an advanced program in Big Data.  Best Data Science training programs teach you how to analyze, collect, store and organize your data using Big Data solutions. Most Big Data training institutes help you understand various data genres and management tools.  You will also learn about Big Data modeling and management, which is the central focus of all Big Data projects. You will have hands-on experience of using data management Systems and tools such as AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL.

Through guided hands-on tutorials, students become familiar with techniques using real-time and semi-structured data examples.

Through guided hands-on tutorials, students become familiar with techniques using real-time and semi-structured data examples.  Medical diagnosis through Big Data is one of the best known real-life applications of Big Data. According to a recent report by World Health Organization, around 6.8 million people die every year as a result of neurological disorders. Traditional diagnosis technologies (e.g. magnetic resonance imaging or electroencephalogram) produce huge quantity data (in size and dimension) for detection, monitoring, and treatment of neurological diseases. Diagnosis becomes difficult as since analysis of those medical big data is performed manually by experts to identify and understand the abnormalities. Medical analytics needs to develop automatic decision systems by utilizing computational intelligence for faster, more accurate and efficient diagnosis, prognosis, and treatment processes. It is here that computerized diagnosis system (CAD) comes as a boon for medical diagnosis and prediction. Computerized diagnosis systems or computer-aided diagnosis systems can automatically detect the neurological abnormalities using the medical big data. This system improves the consistency of diagnosis and ensures better treatment, saving millions of lives and reducing cost and time.

Choosing the Best Data Analytics Courses

If you are planning for a career in Data Analytics, you need to enroll for a Data Analytics Course. But before that, you need to develop your knowledge of Data Analytics and enhance your programming and mathematical skills. A prior knowledge of analytic tools such as Apache Spark and R would be useful.

Do a thorough research on the best Data Analytics Courses offered to find out what works best for you. Most online or class training cover topics like cloud-based Data analysis, predictive analytics, including probabilistic and statistical models, application of large-scale data analysis, analysis of problem space and data needs.

Data Analytics courses will give you a thorough understanding of Big Data applications and fundamental principles used in predictive analytics. You will also learn to develop algorithms for the statistical analysis of Big Data, evaluate and apply appropriate principles, techniques and theories to large-scale Data Science problems.

Career Path in Big Data and Analytics

You may start as a Data Analyst, go on to become a data scientist with some years of experience, and eventually turn out to be a data evangelist. Data Science offers lucrative career options. You may continue as a data scientist or move on to advisory roles in government or private sectors. Many well-known Data Science influencers in India and abroad have started as a data scientist and held leading positions in top-notch brands. Many are often invited as keynote speakers in webinars and tech conferences to share their deep insights on Data Science and Big Data.

Good knowledge of data management, machine learning, and natural language processing solutions and leadership skills are some of the essential requirements for a career in Data Science.

Digital Vidya’s Big Data and Analytics Course

Digital Vidya offers one of the best-known Data Analytics courses for a promising career in Data Science. Its industry-relevant curriculum, pragmatic market-ready approach, hands-on Capstone Project are some of the best reasons for choosing Digital Vidya. In addition, students also get lifetime access to online course matter, 24×7 faculty support, expert advice from industry stalwarts, and assured placement support that prepares them better for the vastly expanding Data Science market.

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A self-starter technical communicator, capable of working in an entrepreneurial environment producing all kinds of technical content including system manuals, product release notes, product user guides, tutorials, software installation guides, technical proposals, white papers, and blogs.

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  • There is 1 comment

    • 2 weeks ago

      peter   /   Reply

      Hey Bonani,
      You have shared a very nice blog with necessary information of choosing Big Data technology!! Keep posting with us..
      Thank you

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