Skills you'll learn:

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

Tools you'll learn:

• Tableau
• SQL
• SSIS
• Gretl

Course Overview

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 whatever 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.

Interestingly, this course is actually in the top 100 Udemy courses of all time, along with many of Kirill's other courses about Machine Learning. Pretty incredible considering Udemy has tens of thousands of courses!

About the Instructor

Kirill Eremenko

Kirill is a data science management consultant that has over five of experience in industries like finance, transportation, and retail.

Today, Kirill utilizes big data to optimize customer experience, drastically improve operations, and to drive overall business strategy.

He's also an avid Forex market trader with a strong interest in algorithmic trading, which he has created a few separate courses on.

Skills you'll learn:

• Python Objects and Data Structures, like strings, sets, tuples, & dictionaries
• Comparison Operators
• Statements, Loops, & List Comprehension
• Methods, Functions, Lambda Functions
• Object Oriented Programming with Python
• Errors and Exception Handling
• Map, Reduce, Filter, and other built-in functions
• Decorators
• Intro to GUIs
• and much, much more!

Tools you'll learn:

• Python 2 & 3
• Jupyter Notebooks
• Intro to Git & Github

Course Overview

One of the best, most well-rounded Python courses I have come across. The instructor really does take you from "zero to hero" by walking you through everything you would need to know to have a firm grasp of Python.

A huge bonus is that Jose, the instructor, is also a data scientist that has several other data-oriented courses on Udemy. This really shows in the curriculum when he starts taking you through some of the more useful data manipulation built-in functions, like filter/map/reduce and list comprehension.

After finishing this course, you'll primed and ready for more in-depth data science with Python.

About the Instructor

Jose Portilla

Jose is a data scientist with an MS in Mechanical Engineering and several years of experience training other data scientists.

He publishes and holds several patents in various fields, like data science tech, microfluids, and materials science.

Jose is currently the head of data science for Pierian Data Inc., and creates data science training for several top companies across the world.

Skills you'll learn:

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

Tools you'll learn:

• Python
• HTML / CSS
• Javascript & JQuery
• Jinja2 Templating
• MongoDB
• REST
• Flask
• Heroku and Digital Ocean

Course Overview

The link to this course will give you a large percentage off courtesy of the instructor, Jose, for LearnDataSci readers.

Even though this course doesn't directly have much to do with data science, I included it as more of a fun way to learn about Python while also learning how to do something else that's useful: build web apps.

The instructor takes you through many of the basics of Python and jumps right into building a web app with Flask.

I consider this skill useful for data scientists since it allows you to seamlessly host your data solutions in the same language you're performing analysis with.

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.

About the Instructor

Jose Salvatierra

A programmer since the age of ten, Jose has worked at several tech companies as a Python developer.

Jose has been teaching computer science for over four years and currently has four Python oriented courses on Udemy with over 17,000 students enrolled to date.

Skills you'll learn:

• 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'll learn:

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

Course Overview

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.

About the Instructor

Frank Kane

Frank spent nine years developing and managing the recommender systems used by Amazon and IMDB.

He currently holds 17 patents in data mining, machine learning, and distributed computing.

Currently, he runs his own successful virtual reality environment tech startup, called Sundog Software.

Skills you'll learn:

• Linear and Logistic Regression
• Supervised and Unsupervised Machine Learning
• How to build a neural net with Python and NumPy
• How to build a neural net with Google's TensorFlow
• The Backpropagation training method
• Bayesian Machine Learning
• Convolutional Neural Networks
• Hidden Markov Models
• Natural Language Processing with Deep Learning

Tools you'll learn:

• NumPy
• TensorFlow

Course Overview

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 already know Python, Calculus, Linear Algebra, and Probability.

You'll learn how deep learning and neural nets are built, and you're walked through concrete examples, like predicting user actions on a website and facial expression recognition, that help solidify the material.

Justin does an excellent job of explaining the intricacies of a somewhat more complex topic and helps the student build a strong base understanding for future projects.

About the Instructor

Justin C

Justin has formally taught both undergrad and grad students on various topics, like machine learning, statistics, algorithms, and data science.

He completed his masters thesis on machine learning for brain-computer interfaces, and moved on to work with advertising companies where he created machine learning models that drive revenue through click-through predictions and recommender systems.

Skills you'll learn:

• 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'll learn:

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

Course Overview

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.

About the Instructor

Jose Portilla

See above...

Skills you'll 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'll learn:

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

Course Overview

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.

About the Instructor

Frank Kane

See above...

Skills you'll 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'll learn:

• Amazon's Elastic MapReduce
• Hadoop YARN
• Spark SQL
• Spark Streaming
• GraphX
• MLlib

Course Overview

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.

About the Instructor

Frank Kane

See above...

Skills you'll 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'll learn:

• All Tableau 10!

Course Overview

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.

About the Instructor

Kirill Eremenko

See above...