Top 8 Udemy Data Science Courses for 2017

Top 8 Udemy Data Science Courses in 2017

2017 is turning out to be a fantastic year for data science courses on Udemy. Instructors work extremely hard to keep their courses updated, and at times putting in a complete overhaul of the course material with no additional cost to the student.

Udemy courses are inherently well-defined for specific topics, and the most of the time the instructors take time to go through real-world examples you can follow along with and add to your portfolio. Learning by creating something real is much more fun and the lessons tend to stick better.

As a side note, Udemy offers a generous 30 day money back guarantee on all of their courses, so 100% guaranteed to love the course or get your money back (some employers will reimburse the fee too).

If you're interested in learning more about ALL of the courses I've come across to date, definitely check out this giant data science course list.

Now let's get to the list! Below you’ll find the most highly rated and recommended data science courses on Udemy for 2017.

Best Intro Data Science Course

Data Science A-Z: Real-Life Data Science Exercises Included

Rating: 4.5 (3.6k ratings)
Instructor: Kirill Eremenko, Data Scientist & Forex Systems Expert
Course Length: 20.5 hours
Price: $35

Skills you will learn

  • Cleaning and preparing data for analysis
  • Data modeling
  • Basic data visualizion
  • Linear and Logical Regression
  • How to use SQL and a SQL server for data analysis

Tools you will learn

  • Tableau
  • SQL
  • SSIS
  • Gretl


If you're just beginning data science, then this is a great course to start with. You'll see pretty much the entire data science pipeline, going from data mining all the way to visualization using Tableau. By the end you'll be able to use techniques like Linear and Logical Regression, validating your data mining with the Chi-Squared test, and a lot more.

The course is uniquely set up in a way such that you can select what ever module interests you the most and start with that instead of going through the whole course in order. So whether you want to mine and visualize data in Tableau, or jump straight to modelling with Regression, it's up to you.

Best Python Course

Complete Python Web Course: Build 8 Python Web Apps

Rating: 4.5 (600+ ratings)
Instructors: Jose Salvatierra, Founder of School of Code and Computer Science instructor
Course Length: 14.5 hours
Price: $30

Skills you will learn

  • Fundamentals of Python
  • How to perform web requests and parse pages
  • How to build web apps with Python and MongoDB

Tools you will learn

  • Python
  • HTML
  • CSS
  • Jinja2
  • Javascript
  • jQuery
  • MongoDB
  • REST
  • Flask
  • Heroku and Digital Ocean


40% off – The link to this course will add a 40% off coupon courtesy of the instructor, Jose, for LearnDataSci readers 🙂

Yes, this is a course on how to build web apps with Python. So why include it here with the other data science courses?

As you're learning Python, you'll get to have some fun by learning concepts that aren't taught in any of the other data science courses.
Here you're learning how to apply Python to create web apps, which comes in handy when you're thinking about how to host your project so others can interact with them.

If you've thought about creating a Software as a Service (SaaS) data product, then definitely check out this course to see how you can use Python to do just that.

Best Machine Learning Courses

Data Science and Machine Learning with Python – Hands On!

Rating: 4.5 (3.5k ratings)
Instructor: Frank Kane, Data Miner and Software Engineer
Course Length: 9 hours
Price: $30

Skills you will learn (in Python)

  • Linear & Multivariate Regression
  • Supervised and unsupervised learning
  • Bayesian Methods
  • K-Means Clustering
  • Support Vector Machines
  • Reinforcement Learning
  • K-Nearest Neighbor
  • Collaborative Filtering
  • Decision Trees & Random Forests
  • Ensemble Learning

Tools you will learn

  • Python machine learning libraries
  • Apache Spark and its MLLib package


Data Science and Machine Learning with Python is a comprehensive walk-through of how to use Python to analyzing large data sets with various machine learning and data mining techniques. There's some bonus material on how to perform machine learning on large amounts of data with Apache Spark and MLLib, which is great to know.

This course does go over some basics in Python in the first module, but quickly jumps into the good stuff. It's recommended that you have some experience with programming/scripting beforehand. You'll also get a handy refresher on statistics and probability, so if you're uneasy about that aspect of machine learning then don't worry, it'll be covered here.

Data Science: Deep Learning in Python

Rating: 4.6 (1k ratings)
Instructor: Justin C, Data scientist and big data engineer
Course Length: 1.5 hours
Price: $50

Skills you will learn (in Python)

  • How to build a neural net with Python and NumPy
  • How to build a neural net with Google's TensorFlow
  • The backpropogation training method

Tools you will learn

  • Python's NumPy
  • TensorFlow


In Data Science: Deep Learning with Python you'll be learning how to write your own Neural Network in Python using NumPy and TensorFlow. Here, you'll need to know Python, how to take derivatives, and how to find log-likelihoods.

This is a great course because you learn how deep learning and neural nets are built, and you're walked through concrete examples that help solidfy the material. Justin does an excellent job of explaining the intricacies of a somewhat more complex topic

Best Python Data Visualization Course

Learning Python for Data Analysis and Visualization

Rating: 4.5 (3.5k ratings)
Instructor: Jose Portilla, Data Scientist
Course Length: 21 hours
Price: $35

Skills you will learn (in Python)

  • How to visualize datasets with Python and Pandas
  • How to work with Jupyter Notebooks
  • Using NumPy to work with arrays
  • How to use Pandas to work with data
  • How to work with Excel, JSON, and HTML in Python
  • How to use Matplotlib and Seaborn with Python to visualize data
  • Natural Language Processing
  • Various Machine Learning techniques

Tools you will learn

  • Pandas, NumPy, Matplotlib, and Seaborn with Python
  • JSON, HTML, and Excel data


Here you'll learn a bit of intro Python programming, but pretty much goes straight into working with arrays in NumPy. Along with NumPy, you'll get a ton of experience learning how to analyze and work with data using Pandas.

This is probably one of the most interesting courses on this list just from the number of incredible examples you start going through at the end of the course. Once you've built up the NumPy and Pandas knowledge, you dive into examples like the Titanic project, stock market analysis, and election analysis. Really great course for those craving to start working on tangible projects.

Best Hadoop Course

Taming Big Data with MapReduce and Hadoop – Hands On!

Rating: 4.5 (1.1k ratings)
Instructor: Frank Kane, Data Miner and Software Engineer
Course Length: 5.5 hours
Price: $30

Skills you will learn

  • MapReduce concepts and how to run jobs with Python and MRJob
  • How to use Amazon's Elastic MapReduce to analyze large data sets
  • Other Hadoop tech like Hive, Pig, and Spark

Tools you will learn

  • MapReduce
  • Hadoop Distributed File System (HDFS)
  • Apache YARN
  • Amazon's Elastic MapReduce
  • Intro to Hive, Pig, and Spark


Like most of the other courses in this list, it's recommended you know scripting/programming before you dive into this one.

This course is full of real-life examples using Hadoop and the various tools mentioned above. Even though it's mostly Python, everything is explained
well enough for someone from any language to understand. The best part about this one is that you'll learn how to run MRJobs on a real Hadoop cluster in the cloud.

Best Apache Spark Course

Taming Big Data with Apache Spark – Hands On!

Rating: 4.6 (1.9k ratings)
Instructor: Frank Kane, Data Miner and Software Engineer
Course Length: 5 hours
Price: $25

Skills you will learn

  • How to use Spark's Resilient Distributed Datasets
  • How to use Python to quickly run and develop Spark jobs
  • How to use Amazon's Elastic MapReduce to analyze large data sets
  • How to take complex analysis problems and create multi-stage Spark scripts

Tools you will learn

  • Amazon'ws Elastic MapReduce
  • Hadoop YARN
  • Spark SQL
  • Spark Streaming
  • GraphX
  • MLLib


From the same instructor as the Taming Big Data with MapReduce and Hadoopcourse above, an equally fantastic intro course to Apache Spark.

Just like in the Hadoop course, you'll get tons of real working examples, you'll be using Python, and you will be running Spark both on desktop and in the cloud. The instructor gets straight to
the point and breaks everything down to make Spark very easy to understand and get started with.

Kane will take you from knowing nothing about Spark to writing your own Spark jobs with Python and deploying them on Amazon Web Services.

Best Tableau Course

Tableau 9 For Data Science: REAL-Life Data Science Exercises

Rating: 4.6 (1.6k ratings)
Instructor: Kirill Eremenko, Data Scientist & Forex Systems Expert
Course Length: 6 hours
Price: $30

Skills you will learn

  • How to connect Tableau to various datasets
  • How to analyze, calculate, and blend data
  • How to create plots and charts for visualizing data

Tools you will learn

  • Tableau!


This is Udemy's top rated Tableau course, and it's perfect for anyone that's never used it, or even experienced users looking to hone their skills.

There's way too many things the instructor goes over to list here, but this course could be regarded as the “zero to hero” of Tableau courses. The lessons are
very well laid out, presented, and built on as you move through the course.


There you have it. The top rated data science courses on Udemy. I hope you enjoy learning from these courses as I did. If you have any suggestions you'd like to add of a course you've taken, or if you've already taken a course I listed, I'd love to here about it in the comments below.

Thanks for reading!

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