35 Best+FREE Coursera Courses for Data Science and Machine Learning in 2024

Coursera is an E-Learning platform that provides thousands of online courses on various subjects. And Coursera has a wide range of Data Science and Machine Learning courses too. That’s why I thought to share the 35 Best Coursera Courses for Data Science and Machine Learning with you. So, give your few minutes to this article and find out the Best Coursera Courses for Data Science and Machine Learning.

Now without any further ado, let’s get started-

Best Coursera Courses for Data Science and Machine Learning

1. Data Science Specialization– Johns Hopkins University

Rating– 4.5/5

Time to Complete- 11 months (7 hours per week)

This is one of the most highly rated and enrolled course series. In this course series, there is a separate section on statistics. And Knowledge of Statistics is mandatory for Data Science.

This Data Science specialization Program is the perfect mixture of theory and practical applications. R programming language is used for all Data Science related tasks. This program has 10 courses.

Courses include-

1. The Data Scientist’s Toolbox
2. R Programming
3. Getting and Cleaning Data
4. Exploratory Data Analysis
5. Reproducible Research
6. Statistical Inference
7. Regression Models
8. Practical Machine Learning
9. Developing Data Products
10. Data Science Capstone

Extra Benefits-

1. You will earn a Shareable Certificate after completing the Data Science specialization Program.
2. Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

1. Those who have beginner-level knowledge in any programming language.
2. And those who want to master skills in Data Science.

Interested to Enroll?

If yes, then check out all details here- Data Science Specialization

2. IBM Data Science Professional Certificate– IBM

Rating– 4.6/5

Time to Complete- 10 months (5 hours per week)

This is also one of the highly enrolled and highly rated course series. This Professional Certificate from IBM is for anyone who wants to start a career in Data Science.

This program consists of 9 courses. These 9 courses will cover all Data Science skills starting from open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning.

To start Professional Certificate from IBM Program, no prior knowledge of Computer Science and Programming is required.

Courses include–

1. What is Data Science?
2. Tools for Data Science
3. Data Science Methodology
4. Python for Data Science and AI
5. Databases and SQL for Data Science
6. Data Analysis with Python
7. Data Visualization with Python
8. Machine Learning with Python
9. Applied Data Science Capstone

Extra Benefits-

1. You will earn a Professional Certificate from Coursera.
2. You will get a Digital Badge from IBM.
3. After completing the Professional Certificate, you will get FREE career resources.

Who Should Enroll?

1. Those who are beginners, with no prior experience in Data Science.
2. And those who are looking to start a new career, or want to change the current one.

Interested to Enroll?

If yes, then check out all details here- IBM Data Science Professional Certificate.

3. Practical Data Science Specialization– DeepLearning.AI

Rating- 4.5/5

Time to Complete- 3 months (If you spend 4 hours/week)

This is an advanced-level data science program. In this program, you will learn the practical skills to effectively deploy your data science projects.

There are only 3 courses in this program, where you will learn how to analyze datasets and train machine learning models with AutoML. Then you will understand how to build, train, and deploy Machine learning pipelines using BERT.

At the end of this course, you will learn a series of performance-improvement and cost-reduction techniques to automatically tune model accuracy, compare prediction performance, and generate new training data with human intelligence.

Courses include–

1. Analyze Datasets and Train ML Models using AutoML
2. Build, Train, and Deploy ML Pipelines using BERT
3. Optimize ML Models and Deploy Human-in-the-Loop Pipelines

Extra Benefits-

1. You will earn a Shareable Certificate.
2. Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

1. Those who have a working knowledge of ML algorithms and principles, are proficient in Python programming at an intermediate level, and are familiar with Jupyter notebooks and statistics.

Interested to Enroll?

If yes, then check out all details here- Practical Data Science Specialization

4. Applied Data Science with Python Specialization– University of Michigan

Rating- 4.5/5

Time to Complete- 5 months ( 7 hours per week)

This specialization program teaches data science through the python programming language. You will get a strong introduction to data science Python libraries, like matplotlib, pandas, nltk, scikit-learn, and networkx.

This course series doesn’t include Statistics needed for Data Science and various Machine Learning algorithms. It focuses on how to use these algorithms in Python.

If you want to learn Statistics first, then consider the Statistics with Python Specialization. In Statistics with Python Specialization, you will learn very important Statistical skills that are required for data science. This Specialization Program consists of 5 Courses.

Courses include-

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

Extra Benefits-

1. You will earn a Shareable Certificate.
2. Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

1. This program is not for Beginners. Those who have Intermediate level knowledge in Data Science can Enroll in this program.
2. And those who have a basic python or programming knowledge.

Interested to Enroll?

If yes, then check out all details here- Applied Data Science with Python Specialization

5.  Data Science: Foundations using R Specialization– Johns Hopkins University

Rating- 4.6/5

Time to Complete- 5 months (If you spend 8 hours/week)

This is a specialization program offered by Johns Hopkins University. This specialization program will teach you foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in R, and conducting reproducible research.

You will learn in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. You will also learn some of the common multivariate statistical techniques used to visualize high-dimensional data. In this specialization program, there are 5 courses.

Courses Details-

1. The Data Scientist’s Toolbox
2. R Programming
3. Getting and Cleaning Data
4. Exploratory Data Analysis
5. Reproducible Research

Extra Benefits-

• You will earn Shareable Specialization and Course Certificates.
• Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

• Those who have some programming experience in any language and have some working knowledge of mathematics up to algebra.

Interested to Enroll?

If yes, then check out the details here- Data Science: Foundations using R Specialization

6. Data Science Fundamentals with Python and SQL Specialization– IBM

Rating- 4.6/5

Time to Complete- 6 months(If you spend 4 hours/week)

This is a specialization program, where you will gain foundational skills required for Data Science, including open source tools and libraries, Python, Statistical Analysis, SQL, and relational databases. 

Throughout this program, you will work on hands-on projects by using real-world data sets. This is a beginner-level course and has 5 courses.

In this specialization program, you will also learn about Relational Database concepts for eg.- SQL, Select statements, sorting and filtering, database functions, accessing multiple tables, etc.

This specialization program has 5 courses.

Extra Benefits-

• You will get a Shareable Certificate and Course Certificates upon completion.
• Along with this, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

• Anyone can enroll because this program doesn’t require any prior knowledge.

Interested to Enroll?

If yes, then check it out here- Data Science: Statistics and Machine Learning Specialization

7. Google Data Analytics Professional Certificate– Google

Rating- 4.8/5

Time to Complete- 6 Months (If you spend 10 hours/week)

This is one of the most popular Data Analyst Certification programs. In this program, you will gain an understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job and an understanding of data-driven decision-making and how data analysts present findings.

In this course, you will also learn how to prepare data for exploration and how analysts use spreadsheets and SQL with databases and data sets. 

Then you will learn how to check and clean your data using spreadsheets and SQL as well as how to verify and report your data cleaning results.

This course also covers how to perform complex calculations on your data to complete business objectives.

You will learn about Tableau, a data visualization platform that will help you create effective visualizations for your presentations. At the end of this course, you will learn how to use RStudio to apply R to your analysis.

There are 8 courses in this certification program.

Courses Include-

1. Foundations: Data, Data, Everywhere
2. Ask Questions to Make Data-Driven Decisions
3. Prepare Data for Exploration
4. Process Data from Dirty to Clean
5. Analyze Data to Answer Questions
6. Share Data Through the Art of Visualization
7. Data Analysis with R Programming
8. Google Data Analytics Capstone: Complete a Case Study

Extra Benefits-

1. You will earn a Shareable Certificate after completing the Data Science specialization Program.
2. Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

• Those who are a beginner and want to gain data analytics skills.

Interested to Enroll?

If yes, then check out all details here- Google Data Analytics Professional Certificate

8. Statistics with R Specialization– Duke University

Rating- 4.6/5

Time to Complete- 7 Months

This specialization program will give you in-depth Statistics knowledge with the help of R. In this program, you will learn how to analyze and visualize data in R and create reproducible data analysis reports, and much more.

R is much better than Python for performing statistical operations. So, if you want to master Statistics, then I would recommend this specialization program. This specialization program contains 5 Courses.

Courses Include-

1. Introduction to Probability and Data with R
2. Inferential Statistics
3. Linear Regression and Modeling
4. Bayesian Statistics
5. Statistics with R Capstone

Extra Benefits-

• You will get a Shareable Certificate and Course Certificates upon completion.
• Along with this, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

• Those who have basic math knowledge. No previous programming knowledge is required for this course.

Interested to Enroll?

If yes, then check out all details here- Statistics with R Specialization

9. Data Science: Statistics and Machine Learning Specialization– Johns Hopkins University

Rating- 4.4/5

Time to Complete- 5 Month

This is another Specialization program dedicated to statistics concepts. In this program, you will learn statistical inference, regression models, machine learning, and the development of data products.

At the end of this program, you will work on Capstone Project, where you will apply the skills learned by building a data product using real-world data. This specialization program uses the R programming language.

There are 5 courses in this specialization program.

Extra Benefits-

• You will get a Shareable Certificate and Course Certificates upon completion.
• Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

• Those who have completed the Data Science: Foundations using R Specialization specialization to gain the right foundation. Or you have a good understanding of R programming.

Interested to Enroll?

If yes, then check out all details here-  Data Science: Statistics and Machine Learning Specialization

10. Deep Learning Specialization– deeplearning.ai

Rating- 4.8/5

Time to Complete- 4 months ( If you spend 5 hours per week)

This course is taught by Andrew Ng. This Deep Learning Specialization is an advanced course series for those who want to learn Deep Learning and Neural networks.

Python and TensorFlow are used in this specialization program for Neural networks. This is the best follow-up to Andrew Ng’s Machine Learning Course.

More than 250,000 learners from all over the globe have already enrolled in this Specialization Program. There are 5 courses in this specialization program.

Courses Include-

1. Neural Networks and Deep Learning
2. Improving Deep Neural Networks: Hyperparameter tuning, Regularization, and Optimization
3. Structuring Machine Learning Projects
4. Convolutional Neural Networks
5. Sequence Models

Extra Benefits-

• You will get a Shareable Certificate. 
• You will get a chance to work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing.
• Along with that, you will get a chance to hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice.

Who Should Enroll?

NOTE- This Specialization Program is not for Beginners. This program is suitable for those-

• Who has some basic understanding of Python.
• Who has a basic knowledge of Linear Algebra and Machine Learning.

Interested to Enroll?

If yes, then check out all details here-Deep Learning Specialization

Now, let’s see some Coursera Free Courses for Data Science and Machine Learning

Coursera Free Courses for Data Science and Machine Learning

11. Foundations of Data Science: K-Means Clustering in Python– University of London

Rating- 4.6/5

Time to Complete- 29 hours

This is a free course offered by Coursera, where you will learn the core concepts of Data Science and covers basic mathematics, statistics, and programming skills.

In this course, you will implement the K-means algorithm using Python programming. This course is a perfect balance between theory and practice and a good and useful course for learning the basics of data science.

Interested to Enroll?

If yes, then check out all details here- Foundations of Data Science: K-Means Clustering in Python

12. Machine Learning– Stanford University

Rating- 4.9/5

Time to Complete- 60 hours

This is one of the Best Online Courses for Machine Learning. This course is created by Andrew Ng the Co-founder of Coursera, and an Adjunct Professor of Computer Science at Stanford University.

This Course provides you with a broad introduction to machine learning, data-mining, and statistical pattern recognition.

All the math required for Machine Learning is well discussed in this course.

This course uses the open-source programming language Octave. Octave gives an easy way to understand the fundamentals of Machine Learning.

Interested to Enroll?

If yes, then check out all details here- Machine Learning

13. Bayesian Statistics: From Concept to Data Analysis– University of California, Santa Cruz

Rating- 4.6/5

Time to Complete- 12 hours

This is a Free to Audit course offered by the University of California, but this course is not for beginners. This course begins with the basics of probability and Bayes’ theorem. Then covers the concepts of statistical inference from both frequentist and Bayesian perspectives.

After that, you will learn methods for selecting prior distributions and building models for discrete data. And in the last, this course covers the conjugate and objective Bayesian analysis for continuous data.

Interested to Enroll?

If yes, then check out all details here-Bayesian Statistics: From Concept to Data Analysis

14. Introduction to Statistics– Standford University

Rating- 4.5/5

Time to Complete-15 hours 

This course is Free to Audit. That means you can access the full course material free of cost.

In this course, you will learn the following topics- Descriptive Statistics, Sampling and Randomized Controlled Experiments, Probability, Sampling Distributions, and the Central Limit Theorem, Regression, Common Tests of Significance, Resampling, Multiple Comparisons.

Overall this course is good for clearing the basics.

Interested to Enroll?

If yes, then check out all details here- Introduction to Statistics

15. Data Science Ethics– University of Michigan

Rating- 4.8/5

Time to Complete- 15 hours

This course is Free to Audit and good for understanding more about the ethics behind data science. In this course, you will get to know about the framework to analyze ethical considerations regarding the privacy and control of consumer information and big data.

This course will cover the following questions- Who owns data, How do we value privacy, How to receive informed consent, and What it means to be fair.

Interested to Enroll?

If yes, then check out all details here- Data Science Ethics

Now, let’s see some FREE Intermediate-Level Coursera Courses for Data Science and Machine Learning–

FREE Intermediate-Level Coursera Courses for Data Science and Machine Learning

S/N	Course Name	Rating	Time to Complete	Provider
16.	Process Mining: Data science in Action	4.7/5	22 hours	Eindhoven University of Technology
17.	Bayesian Statistics: From Concept to Data Analysis	4.6/5	12 hours	UC Santa Cruz
18.	Practical Time Series Analysis	4.6/5	26 hours	The State University of New York
19.	Introduction to Embedded Machine Learning	4.8/5	17 hours	Edge Impulse
20.	Improving your statistical inferences	4.9/5	28 hours	Eindhoven University of Technology
21.	Data Science in Stratified Healthcare and Precision Medicine	4.6/5	17 hours	University of Edinburgh
22.	Machine Translation	4.5/5	27 hours	Karlsruhe Institute of Technology
23.	Computer Vision with Embedded Machine Learning	NA	31 hours	Edge Impulse
24.	Experimentation for Improvement	4.8/5	13 hours	McMaster University
25.	Power and Sample Size for Multilevel and Longitudinal Study Designs	4.4/5	24 hours	University of Florida
26.	Improving Your Statistical Questions	4.9/5	18 hours	Eindhoven University of Technology
27.	Population Health: Predictive Analytics	5.0/5	18 hours	Leiden University
28.	Global Statistics – Composite Indices for International Comparisons	4.6/5	16 hours	University of Geneva
29.	Brain Tumor Classification Using Keras	4.5/5	2 hours	Coursera community
30.	Basic Data Analysis and Model Building using Python	3.6/5	1.5 hours	Coursera community
31.	Forecasting Univariate Time Series with an LSTM	3.5/5	2 hours	Coursera community
32.	Predicting Wine Quality with Random Forest and Scikit-Learn	NA	2.5 hours	Coursera community
33.	Analyzing WhatsApp Chat Data	4.1/5	2 hours	Coursera community
34.	Developing Data Science Projects With Limited Computer Resources Using Google Colaboratory	4.4/5	2 hours	Coursera community
35.	Hands-on Text Mining and Analytics	3.9/5	13 hours	Yonsei University

And here the list ends. I hope these 35 Best Coursera Courses for Data Science and Machine Learning will help you to learn data science concepts. I would suggest you bookmark this article for future referrals. Now it’s time to wrap up.

Conclusion

In this article, I tried to cover the 35 Best Coursera Courses for Data Science and Machine Learning. If you have any doubts or questions, feel free to ask me in the comment section.

All the Best!

Enjoy Learning!

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