Silver Blog, Apr 2017New Online Data Science Tracks for 2017

In 2017 there are many new and revamped data science tracks that are much more comprehensive for beginners than ever before. The tracks are designed to give you the skills you need to grab a job in data science, and some even have a job guarantee.


Coursera has had a ton of new courses and specializations for data analysis, machine learning, programming, etc. Everyone is mostly familiar with the R-focused Data Science Specialization and the very famous Machine Learning Course by Andrew Ng, so I won’t mention those here. I’ll touch on a few of the higher rated, more impressive specializations that are new for 2017 below.

Data Visualization with Tableau Specialization

If you’ve been thinking about learning Tableau for data visualization, or even just data visualization in general, then look no further. This is a full, beginner to advanced series on how to visualize data, create dashboards, and make compelling reports with Tableau.


  • Aggregate Rating: 4.3 out of 5
  • Price: $49/month for certificate
  • Organization: UC Davis
  • Prerequisites: none


  1. Fundamentals of Visualization with Tableau
  2. Essential Design Principles for Tableau
  3. Visual Analytics with Tableau
  4. Creating Dashboards and Storytelling with Tableau
  5. Data Visualization with Tableau Project

Applied Data Science with Python Specialization

A fantastic specialization that has a strong focus on machine learning with Python. You’ll learn all of the most used ML toolkits, like scikit-learn and pandas, as well as extensive lectures on visualization with tools like matplotlib and Seaborn.


  • Aggregate Rating: 4.4 out of 5
  • Price: $79/month for certificate
  • Language: Python
  • Organization: University of Michigan
  • Prerequisites: some programming


  1. Introduction to Data Science in Python
  2. Applied Plotting, Charting & Data Representation in Python
  3. Applied Machine Learning in Python
  4. Applied Text Mining in Python
  5. Applied Social Network Analysis in Python

Strategic Business Analytics Specialization

Get experience with real-world business examples, like finding customer lifetime value, forecasting events, and statistical segmentation of customers. The ultimate goal of this specialization is to get you comfortable gathering and presenting business insights with R.


  • Aggregate Rating: 4.13 out of 5
  • Price: $49/month for certificate
  • Language: R
  • Organization: ESSEC Business School
  • Prerequisites: some programming (R is ideal), knowledge of statistics, familiarity with databases and data analysis techniques, like regression and classification


  1. Foundations of strategic business analytics
  2. Foundations of marketing analytics
  3. Case studies in business analytics with ACCENTURE
  4. Capstone: Create Value from Open Data

Mastering Software Development in R Specialization

From the same team that brought you the original Coursera Data Science Specialization, this new series teaches you how to build effective data science tools for R. By the end, you’ll be able to build R packages and custom visualizations, as well as how to create reusable R code that solve data science problems.

You won’t even need to have any experience with R to start. The first course in this track is dedicated to teaching you everything you need to work with the language, and then you’ll move on to solidifying that knowledge with interesting projects and assignments in R.


  • Aggregate Rating: 4.25 out of 5
  • Price: $39/month for certificate
  • Language: R
  • Organization: Johns Hopkins University
  • Prerequisites: some programming, knowledge of algebra


  1. The R Programming Environment
  2. Advanced R Programming
  3. Building R Packages
  4. Building Data Visualization Tools
  5. Mastering Software Development in R Capstone


The first course I took back in 2015 on edX was an Apache Spark series from U.C. Berkeley, and since then they’ve created a great data science learning ecosystem with their new certifications.

That Spark course is still around, and it’s part of an Xseries, which a sequence of courses similar to a lighter version of a Coursera specialization. Now, they’ve created two new options: MicroMasters and Program Certificates, which provide a much more comprehensive and organized way of preparing you for a career in the topic.

Data Science MicroMasters

The Data Science MicroMasters is a very well-rounded program for data science with Python. You’ll learn the ins and outs of using all the advanced functionality of Python for data analysis, everything you’ll need to know about probability and statistics, the most used and well-known machine learning algorithms (from regression to clustering to deep nets and more), and then you’ll cap it off with using Apache Spark on big data.

Additionally, if you decide to get the certificate for this series and are accepted into the program at Curtin University, it will count towards 25% of the coursework needed for the Masters of Predictive Analytics.


  • Aggregate Rating: Reviews disabled until start
  • Price: $1400 for MicroMasters credential
  • Language: Python
  • Organization: UC San Diego
  • Prerequisites: comfortable with programming, multivariate calculus, linear algebra


  1. Python for Data Science
  2. Statistics and Probability in Data Science using Python
  3. Machine Learning for Data Science
  4. Big Data Analytics Using Spark

Artificial Intelligence MicroMasters

This is an incredibly interesting series that’ll get you ready to work with and be part of the rise of automation and AI. Anyone enthusiastic about mathematics and physics, this is a perfect track to take. With a lot of prerequisites recommended, the Columbia professors get very deep into complex topics.

Also, this MicroMasters also allows the coursework to count towards Masters credits. If you apply and are accepted to the program, this MicroMasters will count towards 25% of the credits needed for the Master of Computer Science program at Columbia University.


  • Aggregate Rating: Reviews disabled until start
  • Price: $1200 for MicroMasters credential
  • Language: Python
  • Organization: Columbia University
  • Prerequisites: programming (Python preferred), multivariate calculus, linear algebra, classical mechanics, statistics and probability


  1. Robotics
  2. Animation and CGI Motion
  3. Artificial Intelligence (AI)
  4. Machine Learning

Microsoft Professional Program Certificate in Data Science

So far, this certificate from edX offers the more courses in its track than anything else from Coursera or edX. This series covers a lot. You’ll go from Excel to SQL to R/Python to Azure, and at the same time cover the math, statistics, and machine learning topics you need as a data scientist. The distinguishing feature of this career track is that you get to choose between R or Python for data analysis after the Excel and SQL lectures.


  • Aggregate Rating: 3.79 out of 5
  • Price: $49-$99 per course
  • Language: Python or R
  • Other Tools: Excel, SQL, Azure
  • Organization: Columbia University
  • Prerequisites: programming, some Excel, understanding of databases, algebra


  • Unit 1: Fundamentals
    1. Data Science Orientation
    2. Querying Data with Transact-SQL
    3. Analyzing and Visualizing Data with Excel OR Analyzing and Visualizing Data with Power BI
    4. Statistical Thinking for Data Science and Analytics
  • Unit 2: Core Data Science
    1. Introduction to R for Data Science Course OR Introduction to Python for Data Science
    2. Data Science Essentials
    3. Principles of Machine Learning
  • Unit 3: Applied Data Science
    1. Programming with R for Data Science OR Programming with Python for Data Science
    2. Applied Machine Learning OR Developing Intelligent Apps
    3. Implementing Predictive Solutions with Spark in Azure HDInsight
    4. Unit 4 – Capstone Project – Cortana Intelligence Competition
    5. Data Science Professional Project


Thanks for reading. I hope you enjoy taking one of the tracks mentioned above. If you didn’t find something, there’s still a ton of courses on Coursera, edX, Udemy, and Udacity not mentioned here. I’ve recently updated the comprehensive list of data science courses over here, but also do browse around on the platforms for any tools or topics you’re interested in. There’s a good chance they have it.

Bio: Brendan Martin is a Partner at Mint Design Company, and Content Writer at LearnDataSci.