12 Best Free Online Courses for Data Science for Beginners in 2024

Best Free Online Courses for Data Science for Beginners

Are you a data science beginner and looking for the Best Free Online Courses for Data Science for Beginners?… If yes, then you are in the right place. In this article, I have listed the 12 best free online courses for data science for beginners. For these courses, You don’t need to pay a single buck

So, give your few minutes to this article and find out the best free online courses for data science for beginners. Now, without any further ado, let’s get started-

Best Free Online Courses for Data Science for Beginners

1. Foundations of Data Science: K-Means Clustering in Python– Coursera

Rating- 4.6/5
Time to Complete- 29 hours

Foundations of Data Science: K-Means Clustering in Python is a free course offered by Coursera. To access this course for free, click on the “Enroll for FREE” option. A new popup window will appear where there are two options- “Purchase Course” and “Full Course, No Certificate“. Choose the second option “Full Course, No Certificate”. And you will be redirected to the course material.

This course has a 5-week study plan. In the first week, you will learn the data science and machine learning basics. Along with that, you will learn k-means clustering.

Week 2 covers the mathematical concepts of machine learning such as mean, variance, and standard deviation. You will also learn basic statistics in Python.

Week 3 is a practical week where you will learn how to work with multidimensional data in Python and learn the matplotlib library. In week 4, you will work on Pandas library for reading, sorting, and filtering the data. Week 5 has one Capstone project.

Most of the Coursera free-to-audit course doesn’t give access to the project and quizzes but in this course, you will have access to the assignments and projects.

Drawback-

  • Doesn’t provide a certificate for the free course.

Interested to Enroll?

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

2. Intro to Data Science– Udacity

Rating- NA
Time to Complete- 2 Months

Intro to Data Science is another completely free course to learn data science with Python. The course begins with the introduction to data science, skills required for data science, Data Science Programming tools, Numpy, and Pandas. The introduction lesson is very detailed and covers essential topics.

I have never seen any free course with such detailed content which is very impressive. After each topic, there is one problem set on that topic. For eg, first, they will teach you Data Wrangling and then there is one problem set on wrangling subway data.

You will also learn the data analysis process and then you will work on analyzing subway data. Next, you will learn Data Visualization and Big Data tools such as MapReduce. Overall, this is a detailed and well-structured free course to learn data science.

Drawback-

  • You will not receive a certificate after completing this course.

Interested to Enroll?

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

3. Intro to Data Analysis– Udacity

Rating- NA
Time to Complete- 6 Weeks

Intro to Data Analysis is a completely free course. The best thing I found in this course was that most of the free course doesn’t cover projects, but in this course, there is one project.

In this project, you have to investigate a dataset. You have to perform data analysis on a given dataset and showcase your results in a visual form.

This course will teach you the data analysis process and popular Python libraries Pandas, Numpy, and Matplotlib. Overall, this is a good course to understand the data analysis basics with hands-on practice.

Drawback-

  • You will not receive a certificate after completing the course.

Interested to Enroll?

If yes, then start learning- Intro to Data Analysis

4. Python For Data Science– Udemy

Rating- 4.4/5
Time to Complete- 3hr 55min

Python For Data Science course is freely available on Udemy. I checked the content of the course by enrolling in the course. And I found that this course has 6 sections.

In the first two sections, you will learn the Python basics such as Python installation, Python variables, identifiers, keywords, numbers, and arithmetic operators.

Next, you will learn if..elif..else and nested if Statement, Control Statement, Python Data Types, String, and List. At the last, you will learn Python Functions.

Overall, this is course is good for learning Python but this course doesn’t cover data science concepts. So, if you want to start from scratch and want to learn Python, this course is good for you. For learning data science, this course is not suitable.

Drawbacks-

  • Doesn’t provide a certificate.
  • Very basic course.

Interested to Enroll?

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

5. Introduction to Data Science- edX

Rating- NA
Time to Complete- 6 Weeks

Introduction to Data Science is a free good course for beginners to understand the basics of data science. This course has 6 modules, where you will learn data science fundamentals, a day in the life of a Data Scientist, and Big Data and Data Mining.

Along with that, you will learn the basics of deep learning and machine learning. This course also has one exercise on exploring the Watson studio.

Drawback-

  • The final project and quizzes are locked for the free course.

Interested to Enroll?

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

6. Machine Learning by Stanford University– Coursera

Rating- 4.9/5
Time to Complete- 60 hours

Machine Learning by Stanford University 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.

To audit this course for FREE, click on the “Enroll for FREE” button. And new popup will appear where they will provide payment details, but at the bottom, you will see an option “Audit the Course”. Click on it. And you will be redirected to the course material.

The name of this course has been changed and now it is Supervised Machine Learning: Regression and Classification.

In this course, you will learn machine learning basics, supervised learning, unsupervised learning, Linear Regression, and Gradient Descent.

Along with that, you will also learn multiple linear regression and feature scaling. The last part of the course covers logistic regression and the problem of overfitting. Overall, this course covers some essential topics of machine learning and data science.

Drawback-

  • All the labs are locked in the free course.

Interested to Enroll?

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

7. Probability and Statistics– Coursera

Rating- 4.6/5
Time to Complete- 16 hours

Probability and Statistics is a good free course for learning Probability and Statistics concepts for data science. To audit this course for free, click on the “Free to Enroll” option. And they will provide two options. Choose the “Full Course, No Certificate” option.

This course has a 6-week study plan. All the quizzes and assignments are available in the free course, which is good. In this course, you will learn probability basics, descriptive statistics, normal distribution, sampling, confidence interval, type I and type II errors, p-values, central limit theorem, and Linear Regression.

Along with the course material, there are various quizzes and assignments in the course.

Drawback-

  • You will not receive a certificate.

Interested to Enroll?

If yes, then check out all details here- Probability and Statistics

8. Intro to Statistics– Udacity

Rating- NA
Time to Complete- 2 Months

Intro to Statistics is a completely FREE course for beginners to learn statistics for data science. When I enrolled in this course to check the content, I found that this is an in-depth course. There are 34 lessons in this course and 5 problem sets.

The content of this course is well-structured and the instructor explains the concepts visually.

Throughout this course, you will learn data visualization concepts, probability, statistics, central limit theorem, confidence intervals, Regression, Correlation, etc.

After completing this course, there is one final exam, where there are 16 questions and you have to answer these questions. Overall, this is a detailed course to learn statistics basics for data science.

Drawback-

  • Doesn’t provide a certificate.

Interested to Enroll?

If yes, then start learning- Intro to Statistics

9. Data Visualization in Tableau– Udacity

Rating- NA
Time to Complete- 3 Weeks

Data Visualization in Tableau free course will teach data visualization using Tableau. Throughout this course, you will learn Data Visualization basics and Tableau.

You will also understand the difference between Exploratory and Explanatory Analyses. At the end of this course, you will learn about how to create a Dashboard and stories in Tableau.

This course has various quizzes on visual encoding, scatter plots, data storytelling, Hierarchies with Trinaand Building Dashboards & Stories with Trina.

Overall, this is a good course to learn the essential step of data science which is data visualization.

Drawback-

  • You will not receive a certificate after completing the course.

Interested to Enroll?

If yes, then start learning- Data Visualization in Tableau  

10. Learn Data Science With R– Udemy

Rating- 4.4/5
Time to Complete- 8hr 42min

Learn Data Science With R is a basic data science course, where you will learn data science using R Programming. This course will cover R Programming basics, R installation, data frames, lists, and how to import data from files.

I enrolled in this course to check the content quality. The explanation needs some improvement. The course is detailed but the instructor needs to improve the explanation.

Drawback-

  • Doesn’t provide a certificate.
  • The explanation is confusing for some students.

Interested to Enroll?

If yes, then check out all details here- Learn Data Science With R

11. SQL for Data Analysis– Udacity

Rating- NA
Time to Complete- 4 weeks

SQL for Data Analysis course is completely free and covers SQL. SQL is essential for data science and data analysis. So, if you want to learn SQL for data science, you can enroll in this course.

This course will cover SQL basics, Joins, and Aggregations. You will also learn how to perform data cleaning using SQL.

SQL Window Functions, SQL Advanced JOINs & Performance Tuning will be also covered in this course. This course has various quizzes where you will practice the concepts learned in the course.

Overall, this course will provide the SQL knowledge required for data science.

Drawback-

  • Doesn’t provide a certificate.

Interested to Enroll?

If yes, then start learning- SQL for Data Analysis

12. Python Basics for Data Science– edX

Rating- NA
Time to Complete- 5 weeks

Python Basics for Data Science is a beginner-friendly free course to learn Python basics. In this course, you will learn Python basics, Python Data Structure, Python Programming fundamentals, how to work with data in Python, and APIs and Data Collection.

This course has quizzes and exercises to practice the learned concepts. This course is good for learning Python basics, not data science.

Drawback-

  • The final exam is locked in the free course.

Interested to Enroll?

If yes, then check out all details here- Python Basics for Data Science

And here the list ends. So, these are the 12 Best Free Online Courses for Data Science for Beginners. I will keep adding more programs and courses to this list.

My Suggestions

Best Data Science Course using Python for BeginnersFoundations of Data Science: K-Means Clustering in Python
Best Data Science Course using R for BeginnersLearn Data Science With R
Best Course to Learn Statistics for Data ScienceIntro to Statistics
Best Course to learn SQL for Data ScienceSQL for Data Analysis
Best Data Visualization CourseData Visualization in Tableau

Conclusion

I hope these Best Free Online Courses for Data Science for Beginners will help you to understand the data science basics. If you have any doubts or questions, feel free to ask me in the comment section.

All the Best!

Enjoy Learning!

Thank YOU!

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