Are you looking for a career as a data scientist?
In this article, you find a list of useful, practical, and comprehensive data science courses taught entirely in Python.
Before jumping into the courses, I’d like to offer you a quick primer on what is data science and how is Python used in data science.
What Is Data Science
Data science is one of the most in-demand skills in the market.
Companies are hiring data scientists to organize and analyze large collections of data to make better business solutions to get a competitive edge.
A competent data scientist is someone who can:
- Ask and identify the right questions.
- Collect data from a variety of useful data sources.
- Organize information.
- Turn results into actual business solutions.
- Communicate the findings for better business decisions.
The cool part is that this is not just some tech industry jargon. These days almost all industries rely on analyzing and making decisions based on data. This makes data science an increasingly valuable skill in the market.
Data scientists use a variety of cutting-edge tools and programming languages to support data analysis. These include:
- Python programming language
- R programming language
- Jupyter Notebook environment
- NoSQL Databases
- Tableau data visualization
- Github version control
Let’s take a closer look at the Python programming language
What Is Python
Python is one of the most popular programming languages to date.
It is a versatile programming language. You can use Python for example in:
- Game development
- Web development
- Mathematics
Most importantly, Python is the go-to language of data science.
Getting started with Python is easy. As a matter of fact, it is commonly recommended as the first programming language to learn.
Due to its easy-to-understand syntax and versatility, it is definitely a language you do not want to miss, no matter which area in software development you are into.
If you are looking for a career as a data scientist, a great place to start is by learning the basics of Python programming.
In this article, you find 10 data science courses taught entirely in Python.
These courses are in no particular order. Some of the courses are more introductory-based, which means you can get a course done in a week or two. However, this list also includes courses that are going to take you from zero to hero in a year or less.
Anyway, I hope you enjoy the list and pick something you find useful!
Disclaimer: This post contains affiliate links.
1. Python for Data Science and Machine Learning Bootcamp – Udemy
Course Overview
Python for Data Science and Machine Learning Bootcamp course teaches you the fundamentals of data science and machine learning.
In this course, you are going to learn how to use cutting edge data science libraries and tools, such as:
The instructor of the course is Jose Portilla who has taught more than 2.5 million students! Commonly, Jose’s courses focus on Python, Deep Learning, Data Science, and Machine Learning.
This self-paced course lasts for 25 hours.
It consists of 150 concise and useful videos explaining different concepts in data science. These include useful topics, such as:
- Python crash course
- Overview of the common data analysis libraries and tools
- Common machine learning algorithms
- Data visualization
And much more.
Course Highlights
- Using Pandas for data analysis.
- Using Seaborn and Matplotlib for data visualization.
- Understanding machine learning fundamentals such as
- Logistic regression
- Neural networks
- Linear regressions
- Using Scikit-Learn for machine learning.
- Create in-built interactive and dynamic visualization to visualize patterns in datasets.
- Understanding natural language processing and spam filtering.
Who Is the Course for?
This course is a must for someone who is interested in data science and has some programming skills, to begin with. The course is taught entirely by using the popular Python programming language and its libraries.
It is good if you know some Python before getting started.
However, knowing the basics of any programming language suffices. This is because the different programming languages still operate on the same principles.
Anyway, the course starts with a Python crash course, so you have a chance to learn or revise your Python skills during that time.
After completing the course, you get a nice certificate to showcase your skills to future recruiters.
Rating: 4.7
Participants: 500,000+ students
Duration: ~25 hours
2. Complete Data Science Training with Python for Data Analysis – Udemy
Course Overview
Complete Data Science Training with Python for Data Analysis is a concise and thorough course to learn data science with Python.
The course lasts 12 hours and is taught by Minerva Singh, who has taught more than 75,000 students!
During the 12 hours, you learn the basics of important concepts around data science, including:
- Statistical modeling
- Data visualization
- Deep learning
When it comes to data science, you also need to know how to handle large amounts of data. This course has got your back!
You are going to learn how to use Python’s popular data science packages to:
- Storing data
- Mining data
- Cleaning data
- Manipulating data
Overall, this course prepares you for using data science in the real world to solve real problems with data.
Course Highlights
- Install Anaconda
- Learn how to use Jupyter Notebook.
- Web scraping & cleaning data.
- Learn statistical methods, such as linear regression or logistic regression.
- Learn how to implement supervised and unsupervised learning techniques on real data.
- Explore data by tabulating, pivoting, and data summarizing.
- Learn about neural networks and deep learning algorithms
Who Is the Course for?
This course is for someone with no previous knowledge of Python or machine learning. With the help of 24/7 mentors and real-life projects, you are going to become proficient at machine learning and deep learning.
After successfully completing the course, you get a certificate for showing your expertise!
Rating: 4.4
Participants: 8,000+
Duration: ~13 hours
3. Python A-Z™: Python For Data Science With Real Exercises!– Udemy
Course Overview
Python A-Z is an introductory-level course in data science. It teaches you the basics of the in-demand skills in data science. After completing the course you can apply these skills in solving real-life business problems.
The course is taught by a data scientist, Kirill Eremenko, who has taught more than 2 million students!
In this course, you are going to learn important concepts such as:
- Data mining
- Statistical analysis
- Data visualization
You are also going to learn the basic principles of Python programming.
The programs are written in Jupyter Notebooks.
A Jupyter Notebook is a popular web application for data scientists. You can use a Jupyter Notebook to create and share documents with live code, equations, visualizations, and other useful resources.
You are going to learn the fundamentals of Python programming. These include:
- Variables
- Loops
- Data types
- Functions
These concepts are important because they help you collect, store, and analyze data.
Course Highlights
- Learn how to read & write Python programs.
- Understand Python basics.
- Learn to use Python packages and Jupyter Notebook.
- Use dataframes to import data into your Python program.
- Data visualization with Seaborn.
Who Is the Course for?
Python A-Z is a course that best suits someone with any academic background. You do not need to possess any programming skills to get started.
After successfully completing the course, you get a certificate. You can then showcase it to your recruiters.
Rating: 4.6
Participants: 130,000+
Duration: ~11 hours
4. Programming for Data Science with Python – Udacity
Course Overview
Data Science with Python is an online course taught by Udacity. It is a course that prepares you for a career as a data scientist.
You are going to learn how to use:
Let me briefly explain why each of these skills is so important.
Python
Python is one of the most in-demand languages to date. It is really popular among data scientists.
Python is a language that is easy to get started with. It sometimes reads like English.
Python is a go-to language when it comes to data science and analysis.
With Python, you collect, clean, operate, analyze, and visualize data.
SQL
SQL is used to communicate with a database that holds data related to your program. SQL is a language that is used to perform tasks, such as update/retrieve database data.
When dealing with data, it is important to be able to store the data for easy access. This is why SQL is also taught in this course.
Command Line
Command-line is a text-based interface to a computer. You can use a command line to write instructions to the computer. The command line then executes these instructions right away.
You can use the command line for so many things. However, when it comes to data science, the command line is useful for:
- Version control (Git)
- Running Python programs
- File management
Git
Git is the most popular version control system for your programming projects.
Learning how to use Git (and Github) is inevitable if you want to build a career as a data scientist. This is because Git makes it possible for teams to work on the same project simultaneously.
Instead of copy-pasting your changes in code and sending them to your colleagues, you merge the changes to the codebase from your branch.
Git stores the history of your projects. If you want to reset your piece of code to where it was 3 months ago, no problem.
Anyway, it is important to learn Git sooner or later.
It is awesome that this course teaches you how to use Git!
Course Highlights
- Learn how to perform SQL queries.
- Understand Python programming basics.
- Use popular Python libraries to operate on data.
- Get real-life experience with the hands-on projects.
- Get feedback from experienced reviews.
- Share your work on Github to showcase your passion.
Who Is the Course for?
Data Science with Python is a beginner-friendly course. It has no prerequisites. If you are interested in data science and you know how to use a computer, that is enough.
Rating: 4.8 (~1400 reviews)
Duration: ~120 hours
5. Applied Data Science with Python Specialization–Coursera
Course Overview
Data Science Specialization is a thorough introductory course to data science and Python.
This course is taught by a well-known Professor Christopher Brooks, who has taught close to 700,000 students. In addition, there are 3 other skilled data science experts teaching the course too.
The Data Science Specialization consists of 5 different courses. To become an expert in data science, you need to complete all five courses.
After completing the Data Science Specialization, you know how to implement:
- Statistical analysis
- Text analysis
- Information visualization
- Social network analysis
To make all this possible, you are going to learn how to use the common Python toolkits for data science, including:
- Scikit-Learn
- Pandas
- Matplotlib
And so much more.
Course Highlights
- Learn Python programming basics in data science, such as data manipulation and cleaning for statistical analysis.
- Learn how to draw plots, and charts, and do all sorts of data visualization in Python.
- Understand how to improve your data analysis strategies with applied machine learning methods.
- Use the nltk framework for text mining and manipulation in Python.
- Understand the basics of network analysis and connectivity of networks.
- Work with hands-on projects.
Who Is the Course for?
If you are serious about a career as a data scientist without any previous knowledge in data science or programming, this bunch of courses is for you.
After completing the courses you receive a certificate from the University of Michigan for showcasing what you have learned.
Rating: 4.5
Participants: 300,000+
Duration: ~140 hours
6. Introduction to Data Science in Python– Coursera
Course Overview
Introduction to Data Science in Python is part of the previously mentioned Applied Data Science with Python Specialization track.
This introductory-level course is taught by Professor Christopher Brooks, and 3 other skilled tutors.
After completing the course, you know how to:
- Obtain data.
- Clean the data.
- Manipulate data.
- Run statistical analysis on the data.
These skills are super useful when it comes to data science and statistical analysis. Without knowing how to operate on large amounts of data efficiently, there is no way you can be a data scientist. More importantly, you learn some valuable Python skills, that are essential for anyone seeking a job as a data scientist.
Course Highlights
- Setting up and using the Python environment.
- Learning the fundamentals in Python.
- Handling CSV files.
- Using NumPy library.
- Data cleaning & manipulation techniques
- Abstraction of the Series and DataFrame in data analysis
- Using functions like groupby or merge.
Who Is the Course for?
If you want to become a data scientist, a great place to start is by attending an introductory course in Python & data science.
Also keep in mind that this course is a part of a bigger track, the Applied Data Science with Python Specialization (previous chapter in this article). If you are serious about data science, I recommend you choose the whole track with its five courses.
Rating: 4.6
Participants: ~650,000
Duration: ~31 hours
7. Python for Data Science, AI & Development – Coursera
Course Overview
Python for Data Science, AI & Development course is designed by IBM. It is taught by Joseph Santarcangelo, who works as a data scientist at IBM.
This introductory-level course in Python is a go-to course for someone interested in learning Python and data science.
Python is a beginner-friendly language. Its versatility makes it applicable to almost anything. More importantly, Python is the language of data science, artificial intelligence, and machine learning. Thus it is something you really want to get used to when jumping into the world of data science.
In this course, you learn the basics of Python programming, including useful skills including:
- Retrieving data
- Operating on data
- Visualizing data
These skills help you become a skilled data scientist who can make better business solutions.
The topics of this course include Python programming fundamentals, such as:
- Variables
- Loops
- Data structures
- Algorithms
- Storing data
To learn to program, you have to get these basics right!
Course Highlights
- Installing Python on your system.
- Writing your first Python program.
- Understanding how to store data in a Python program.
- Writing common code constructs, such as loops, functions, and classes.
- Reading and writing files into Python program.
- Learning about common Python libraries to help you as a data scientist.
- Use web scraping and APIs to retrieve data from the internet.
Who Is the Course for?
This course is best for someone with zero previous knowledge of programming.
If you want to become a data scientist, a great place to learn is by attending a Python course.
Completing this course will earn you a certificate from Coursera + a cool badge from IBM.
Rating: 4.6
Participants: ~370,000
Duration: 19 hours
8. Introduction to Python – Datacamp
Course Overview
Introduction to Python teaches you the fundamentals of data analysis in Python.
This course is massively popular and has close to 4 million participants!
The course is split into four parts:
- Python Basics
- Python Lists
- Functions and Packages
- NumPy
It is a great start for someone who is interested in a career as a data scientist.
This course teaches you how to use the popular data analysis library NumPy to store and manipulate data. This course was built by Hugo Bowne, whose intention was to make the students gain a competitive edge in the field.
Course Highlights
- Get your first touch with Python programming, such as variables and datatypes.
- Learn about Python functions, loops, packages, and libraries.
- Learn how to handle data by storing, cleaning, and manipulating it.
- Learn how to use NumPy, a powerful data science tool in Python.
- Handle huge amounts of data efficiently.
- Work with baseball and football match data.
Who Is the Course for?
The course best suits someone with basic programming skills or who wants to get started on a career in Data Science.
Duration: 19 hours
Participants: ~4,000,000
9. Python Basics for Data Science – edX
Course Overview
Python Basics for Data Science is an introductory-level course taught by edX. It offers you a great introduction to the Python programming language, which is a popular programming language in the field of data science.
This course was put together by IBM and is taught by Joseph Santarcangelo, Ph.D. Data Scientist at IBM.
This self-paced course is split into 5 modules:
- Python basics
- Python data structures
- Python programming fundamentals
- Working with data in Python
- Working with NumPy Arrays
Course Highlights
- Learn what is Python and why is it popular in the field of data science.
- Apply Python in data science
- Python basics, such as variables, functions, and data types.
- Learn how to handle files in your Python program (read, write)
- How to use the go-to data analysis package called Pandas.
Who Is the Course for?
This course is for someone without previous knowledge in programming or data science. Some basic maths is required, though.
After completing the course, you can earn a skill badge to prove what you have learned throughout the course.
Duration: 20-30 hours
10. Data Science with Python Certification Course– Simplilearn
Course Overview
Data Science with Python Certification is a comprehensive course that teaches you important topics in data science and analysis.
In this course, you are going to learn valuable skills, such as:
- Data analysis
- Machine learning
- Data visualization
- Web scraping
- Natural language processing
All these skills are trending right now, and are in high demand in the job market. With the help of these skills, you are going to be able to solve real-life business problems using actual data.
Here are some highlights of the course.
Course Highlights
- It gives an overview of concepts of data science and data analytics.
- Learn about Statistical Analysis and Business Applications.
- Set up a Python Environment and learn to write programs.
- Understand how Numpy and Scipy work for scientific and mathematical computing.
- Use Pandas for data manipulation to get insights to solve problems.
- Import Scikit-learn library for machine learning and natural language processing.
- Create interactive and dynamic data visualization using Matplotlib.
- Practice integrating Python with Hadoop MapReduce and Spark.
Who Is the Course for?
The course is best suited for students who want to take a leap towards a career as a data scientist.
As a pre-requisite, it is advised you know some basic maths and programming.
To get most of this course, it is recommended you first get started with the Simplilearn companion courses including:
- Introduction to Data Science in Python
- Math Refresher
- Data Science in Real Life
- Statistics Essentials for Data Science
At the end of the course, you will receive a certification to prove your skills to the recruiters.
Rating: 4.5
Participants: 30,000+
Duration: 68 hours