28 Best Online Data Science Courses- Complete Guide for 2025

Are you looking for Best Online Data Science Courses?… If yes, then this article is for you. This article is a complete guide for you. In this article, you will find the 28 Best Online Data Science Courses for Beginners, Intermediate, and Advanced learners. Along with that, you will find some best free data science courses, and a step-by-step data science roadmap. In the end, you will get to know the best programming language for data science.

So, read this full article and grab all essential information regarding Data Science. Now without further ado, let’s get started with Best Online Data Science Courses–

Best Online Data Science Courses

So, this is the summary of Best Online Data Science Courses.

Now, let’s start this article with the Best data science courses for beginners–

Best Data Science Courses for Beginners

1. Data Science for Everyone– Datacamp

Time to Complete- 4 hours

This is a beginner-friendly course, where you will learn about the basics of data science like Introduction to Data Science, data science workflow, Data preparation, and experimentation and prediction. If you are a beginner, then this is the best course to begin your data science journey.

There are 4 chapters in this course-

1. Introduction to Data Science
2. Data Collection and Storage
3. Preparation, Exploration, and Visualization
4. Experimentation and Prediction

Who Should Enroll?

• Those who are a beginner in data science.

Interested to Enroll?

If yes, then check out the course details here- Data Science for Everyone

2. Programming for Data Science with Python– Udacity

Time to Complete- 3 months( If you spend 10 hrs/week)

This is a Nanodegree program offered by Udacity for data science beginners. In this Nanodegree program, you will learn how to represent and store data using Python data types and variables. You will also use conditionals and loops to control the flow of your programs.

By using complex data structures like lists, sets, dictionaries, and tuples, you will store collections of related data. You will also learn two powerful Python libraries – Numpy and Pandas.

Extra Benefits-

• You will get a chance to work on real-world projects with industry experts.
• You will get Project feedback from experienced reviewers.
• And you will also get Technical mentor support.

Who Should Enroll?

• Anyone can enroll in this program who has basic computer skills.

Interested to Enroll?

If yes, then check it out here- Programming for Data Science with Python

3. IBM Data Science Professional Certificate– Coursera

Rating– 4.6/5

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

This Professional Certificate from IBM is for anyone who wants to start a career in Data Science with Python.

This program has 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. In this certification program, you will work on the following projects-

• Random album generator,
• Predict housing prices,
• Best classifier model,
• Battle of neighborhoods.

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 a beginner, 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

4. The Data Science Course 2025: Complete Data Science Bootcamp– Udemy

Time to Complete- 28.5 hours

This is the best course, I have found on Udemy. Why…? because this course tries to cover almost all necessary topics of data science. This course covers the following topics- Intro to data science, statistics, and mathematics required for data science, Python, Tableau, machine learning, and deep learning.

Extra Benefits-

• You will get a Certificate of Completion.
• Along with that, you will get lifetime access to the course material.

Who Should Enroll?

• Those who are beginners in data science.

Interested to Enroll?

If yes, then check out the course details here- The Data Science Course 2020: Complete Data Science Bootcamp

5. Professional Certificate in Data Science– edX

Provider- Harvard University

Time to Complete- 1 year 5 months ( If you spend 3 hours per week)

In this program, you will learn probability, inference, regression, and machine learning. Along with this, you will learn an essential skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with Unix/Linux, version control with git, and GitHub, and reproducible document preparation with RStudio.

Each course contains case studies such as Trends in World Health and Economics, US Crime Rates, The Financial Crisis of 2007-2008, Election Forecasting, Building a Baseball Team (inspired by Moneyball), and Movie Recommendation Systems.

Along with this, you will also learn R, statistical concepts, and data analysis techniques. 

Who Should Enroll?

• Anyone can enroll. There is no prerequisite.

Interested to Enroll?

If yes, then check out the program details here- Professional Certificate in Data Science

So, these are the 5 Best data science courses for beginners in the “Best Online Data Science Courses List”. Now, let’s move to the best intermediate data science courses–

Best Intermediate Data Science Courses

6. Applied Data Science with Python Specialization– Coursera

Provider- 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.

Skills Gain-

1. Text Mining
2. Python Programming
3. Data Cleansing
4. Data Virtualization
5. Data Visualization (DataViz)
6. Machine Learning (ML) Algorithms
7. Natural Language Toolkit (NLTK)

Courses include-

This Specialization Program consists of 5 Courses-

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, and 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. The one, who has basic python or programming knowledge.

Interested to Enroll?

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

7. MicroMasters^® Program inData Science– edX

Provider- UCSanDiego

Time to Complete- 10 months (9-11 hours per week)

In this program, you will learn the mathematical and computational tools that form the basis of data science. You will also learn how to use those tools to make data-driven business recommendations.

This program has two sides to data science learning- mathematical and applied.

In the mathematics course, you will learn probability, statistics, and machine learning. And in applied, you will get to know about Python, Numpy, Matplotlib, pandas and Scipy, the Jupyter notebook environment, and Apache Spark.

This program has 4 courses. Now let’s see the details of the courses-

Courses Include-

1. Python for Data Science
2. Probability & Statistics in Data Science using Python
3. Machine Learning Fundamentals
4. Big data analytics using Spark

Who Should Enroll?

• Who is familiar with programming languages and has a basic understanding of high-school-level math.

Interested to Enroll?

If yes, then check out the program details here- MicroMasters^® Program inData Science

8. Data Engineering, Big Data, and Machine Learning on GCP Specialization– Coursera

Provider- Google Cloud

Rating- 4.5/5

Time to Complete- 2 months ( 12 hours per week)

This Specialization program offered by Google Cloud gives a hands-on introduction to designing and building data pipelines on the Google Cloud Platform. It is combined with presentations, demos, and hands-on labs.

Skills Gain-

1. How to design and build data pipelines on the Google Cloud Platform?
2. How to Lift and shift your existing Hadoop workloads to the Cloud using Cloud Dataproc.
3. You will learn Process batch and streaming data.
4. How to manage your data Pipelines with Data Fusion and Cloud Composer.
5. You will learn how to derive business insights from extremely large datasets using Google BigQuery.

Courses include-

This Specialization Program consists of 5 Courses-

1. Google Cloud Platform Big Data and Machine Learning Fundamentals
2. Modernizing Data Lakes and Data Warehouses with GCP
3. Building Batch Data Pipelines on GCP
4. Building Resilient Streaming Analytics Systems on GCP
5. Smart Analytics, Machine Learning, and AI on GCP

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, and Graded Programming Assignments.

Who Should Enroll?

1. Those who have Intermediate level knowledge in Data Science.

Interested to Enroll?

If yes, then check out all details here-Data Engineering, Big Data, and Machine Learning on GCP Specialization

9. Python for Data Science and Machine Learning Bootcamp– Udemy

Rating- 4.6/5

Time to Complete- 25 hours

This is one of the best Udemy courses on Data Science with Python. In this course, you will learn how to program with Python, how to create data visualizations, and how to use Machine Learning with Python. You will also learn about Python libraries such as NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, Tensorflow, etc.

Along with that, you will learn machine learning algorithms including Linear Regression, K Nearest Neighbors, K Means Clustering, Decision Trees, Random Forests, Natural Language Processing, Neural Nets, Deep Learning, Support Vector Machines, etc.

Extra Benefits-

• You will get a Certificate of completion.
• Along with that, you will get 5 downloadable resources and Lifetime access to the course material.

Who Should Enroll?

• Those who have some programming experience and want to learn Data Science with Python.

Interested to Enroll?

If yes, then check it out here-  Python for Data Science and Machine Learning Bootcamp

10. Data Science: Statistics and Machine Learning Specialization– Coursera

Rating- 4.6/5

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

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, and Graded Programming Assignments.

You Should Enroll if-

• 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

So, these are the 5 best intermediate data science courses in the “Best Online Data Science Courses List”. Now, let’s move to the best-advanced data science courses–

Best Advanced Data Science Courses

11. Become a Data Scientist– Udacity

Rating- 4.7/5

Time to Complete- 4 months( If you spend 10 hrs/week)

This is a Nano-Degree Program offered by Udacity. This is an advanced-level program. In this program, you will learn how to solve Data Science Problems using Python Programming, Software Engineering Skills, and Data Engineering skills.

The Udacity Data Science Nanodegree program is more practical than other courses. The content of this Nanodegree program is advanced and updated, combined with Real-World problems created by the leaders in the industry. Throughout the Nanaodegree program, you will work on the following 4 different projects–

1. Write a Data Science Blog Post
2. Build Disaster Response Pipelines with Figure Eight
3. Design a Recommendation Engine with IBM
4. Data Science Capstone Project

Extra Benefits-

• You will get a chance to work on real-world projects with industry experts.
• You will get Project feedback from experienced reviewers.
• You will also get Technical mentor support.

Who Should Enroll?

Those who are planning to switch their career to Data Science and are comfortable with the following concepts-

• Python programming, including common data analysis libraries (NumPy, pandas, Matplotlib).
• SQL programming
• Statistics (Descriptive and Inferential)
• Calculus
• Linear Algebra
• Experience wrangling and visualizing data

Interested to Enroll?

If yes, then check out the details here- Become a Data Scientist Program

12. Data Science Specialization– Coursera

Provider- Johns Hopkins University

Rating– 4.5/5

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

This is also 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. You will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data.

You will also learn regression analysis and special cases of the regression model, ANOVA, and ANCOVA. Then you will learn machine learning basics and how to create a data product. 

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. In this specialization program, there are 10 courses.

Courses Details-

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-

• 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, and Graded Programming Assignments.

Who Should Enroll?

• Those who have previous working knowledge in any programming language.

Interested to Enroll?

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

13. Advanced Statistics for Data Science Specialization-Coursera

Rating- 4.5/5

Provider- Johns Hopkins University

Time to Complete- 5 months( If you spend 2 hrs/week)

This is an advanced-level specialization program for data science. In this program, you will learn the advanced concepts of statistics and understand the behind-the-scenes mechanism of key modeling tools in data science, like least squares and linear regression.

In this course, you will get a firm foundation in the linear algebraic treatment of regression modeling, which will greatly augment applied data scientists’ general understanding of regression models. There are 4 Courses in this Specialization.

Courses Details-

1. Mathematical Biostatistics Boot Camp 1
2. Mathematical Biostatistics Boot Camp 2
3. Advanced Linear Models for Data Science 1: Least Squares
4. Advanced Linear Models for Data Science 2: Statistical Linear Models

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, and Graded Programming Assignments.

Who Should Enroll?

• Those who have previous knowledge in basic calculus and linear algebra.

Interested to Enroll?

If yes, then check out the details here- Advanced Statistics for Data Science Specialization

14. Practical Statistics– Udacity

Rating- NA

Provider- Mode

As the name sounds, “Practical Statistics“, this course is focused on the practical implementation of statistical concepts. In this course, you will understand how to tackle common real-world challenges, such as analyzing AB tests and building regression models.

In this course, there is a project, where you have to use statistical techniques to answer questions about the data and report your conclusions and recommendations in a report. Dataset will be provided.

Topics covered in this course are- Simpson’s Paradox, Probability, Binomial Distribution, Conditional Probability, Bayes Rule, Standardizing, Sampling Distributions, and Central Limit Theorem, confidence intervals, Hypothesis Testing, T-Tests, and A/B Tests, Regression, multiple linear regression, and logistic regression.

Extra Benefits-

• You will chance to work on real-world projects with industry experts.
• You will get Project feedback from experienced reviewers.
• You will also get Technical mentor support.

Who Should Enroll?

• Those who have experience working with SQL and with data in Python.

Interested to Enroll?

If yes, then check out all details here- Practical Statistics

15. Data Warehousing for Business Intelligence Specialization– Coursera

Rating- 4.5/5

Provider- University of Colorado System

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

This specialization is for Advanced level Data Engineers. In this program, you will gain data architecture skills that are increasingly critical across a broad range of technology fields.

This specialization will cover the basics of structured data modeling, gain practical SQL coding experience, and develop an in-depth understanding of data warehouse design and data manipulation.

Along with this, you will get a chance to use MicroStrategy, a leading BI tool, OLAP (online analytical processing), and Visual Insights capabilities to create dashboards and Visual Analytics.

This specialization is a 5-course series. Let’s see the course details-

Courses List-

1. Database Management Essentials
2. Data Warehouse Concepts, Design, and Data Integration
3. Relational Database Support for Data Warehouses
4. Business Intelligence Concepts, Tools, and Applications
5. Design and Build a Data Warehouse for Business Intelligence Implementation

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, and Graded Programming Assignments.

Who Should Enroll?

• Those who have some prior experience with software engineering and business intelligence.
• This specialization is especially for software engineering professionals seeking to enter the fields of data engineering, architecture, or big data analytics.

Interested to Enroll?

If yes, then check out all details here- Data Warehousing for Business Intelligence Specialization

So, these are the 5 best-advanced data science courses in the “Best Online Data Science Courses List”. Now, let’s move to the best free data science courses–

Best FREE Data Science Courses

16. Intro to Data Science– Udacity

Time to complete- 2 Months

This is another completely free course to learn data science with Python. In this course, you will learn the fundamentals of data science, data wrangling, normal distribution, data visualization, and the basics of MapReduce.

In this course, you will work on a data science project end to end, from analyzing a dataset to visualizing and communicating your data analysis.

Interested to Enroll?

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

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

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

18. Intro to Data Analysis– Udacity

Time to Complete– 6 Weeks

This is a completely free course and a good first step towards understanding the data analysis process. In this course, you will learn the entire data analysis process including posing a question, data wrangling, exploring the data, drawing conclusions, and communicating your findings. This course will also teach Python libraries NumPy, Pandas, and Matplotlib.

Interested to Enroll?

If yes, then start learning- Intro to Data Analysis

19.  Python For Data Science– Udemy

Rating- 4.4/5

Time to complete- 3hr 55min

This course teaches the Python basics for data science. And this course is good for those who are Data Science, Artificial Intelligence, Machine Learning, and Deep Learning Aspirants. This is not an advanced-level course, but good for understanding the Python basics.

Interested to Enroll?

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

20. Introduction to Data Science– edX

Time to Complete- 6 Weeks

This free course is good for beginners to understand the basics of data science such as tools and algorithms used daily, skills needed to be a successful data scientist, the role of data science within a business, etc.

Interested to Enroll?

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

So, these are the 5 best free data science courses in the “Best Online Data Science Courses List”. Now, let’s move to the other best data science course for specific skills-

Other Best Data Science Courses for Specific Skills

21. 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.

Extra Benefits-

• You will get a Shareable Certificate. Along with that, you will learn various case studies and applications. That will teach you how to apply machine learning algorithms to building smart robots.
• You will also learn text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and others.

Who Should Enroll?

• This Course is Most Suitable for Complete Beginners. But people with some basic understanding of ML can also enroll.

Interested to Enroll?

If yes, then You can Sign Up here.

22. Deep Learning Specialization– Coursera

Rating- 4.8/5

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

This course is taught by Andrew Ng, the co-founder of Coursera and an Adjunct Professor of Computer Science at Stanford University. This is a Specialization Program that contains 5 courses.

This Deep Learning Specialization is one of the best advanced deep learning course series, especially for those who want to learn Deep Learning and Neural networks.

In this specialization program, you will learn Python and TensorFlow for Neural networks. And 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.

Extra Benefits-

• You will get a Shareable Certificate. 
• You will get a chance to work on case studies on 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 have some basic understanding of Python.
• And those who have a basic knowledge of Linear Algebra and Machine Learning.

Interested to Enroll?

If yes, then check here- Deep Learning Specialization

23. Mathematics for Machine Learning Specialization– Coursera

Rating- 4.4/5

Provider- Imperial College London

Time to Complete- 4 Months (4 hours/week)

This is one of the best specialization programs that covers all mathematical topics required for Machine Learning. The aim of this specialization program is to fill the gap and build an intuitive understanding of mathematics.

This specialization program is a 3-course series. In the first course, you will learn Linear Algebra, vectors, matrices, and how it relates to data.

The Second Course of this specialization is Multivariate Calculus. In this course, you will get a deeper understanding of how to optimize fitting functions to get good fits to data.

The last course of this specialization program is Dimensionality Reduction with Principal Component Analysis. This course uses the mathematics from the first two courses to compress high-dimensional data. Along with that, you will work on different real-world projects.

After completing this specialization program, you will have gained the prerequisite mathematical knowledge to continue your Machine Learning journey. Let’s see the details of the courses-

Courses Include-

1. Mathematics for Machine Learning: Linear Algebra
2. Mathematics for Machine Learning: Multivariate Calculus
3. Mathematics for Machine Learning: PCA

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, and Graded Programming Assignments.

You Should Enroll if-

• You have High school level maths knowledge. And basic knowledge of Python and NumPy is required for Course 3.

Interested to Enroll?

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

24. Statistics with R Specialization– Duke University

Rating- 4.6/5

Provider- Coursera

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. Let’s see the course details-

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, and Graded Programming Assignments.

You Should Enroll if-

• You 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

25. Data Visualization with Tableau Specialization– Coursera

Rating- 4.6/5

Provider- University of California, Davis

Time to Complete- 6 months (If you spend 3 hours/week)

In this specialization program, you will learn Data Visualization with Tableau. Tableau is the most powerful, secure, and flexible end-to-end analytics platform for your data. Audi, Bank of America, Amazon, Burger King, EY, and Kimberly-Clark Corporation are a few of the top companies using Tableau

This specialization program is dedicated to newcomers to data visualization with no prior experience using Tableau. In this specialization program, you will see examples from real-world business cases and journalistic examples from leading media companies.

After completing this Tableau Specialization program, you will be able to generate powerful reports and dashboards. And this will help people to make decisions and take action based on their business data. 

This Specialization program is a 5 Course Series. Let’s see the course details-

Courses Include-

1. Fundamentals of Visualization with Tableau
2. Essential Design Principles for Tableau
3. Visual Analytics with Tableau
4. Creating Dashboards and Storytelling with Tableau
5. Data Visualization with Tableau Project

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, and Graded Programming Assignments.

You Should Enroll if-

• You are a beginner in data visualization but comfortable in working with data and datasets.

Interested to Enroll?

If yes, then check out all details here- Data Visualization with Tableau Specialization

26. Learn SQL Basics for Data Science Specialization– University of California, Davis

Rating- 4.6/5

Time to Complete- 4 months

This specialization program is dedicated to those who have no previous coding experience and want to develop SQL query fluency. In this program, you will learn SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, and more. 

This Specialization program is a 4-course series.

Skills Gain-

• Data Analysis
• Apache Spark
• SQL
• Data Science
• Sqlite
• A/B Testing
• Query String
• Predictive Analytics
• Presentation Skills
• Creating metrics
• Exploratory Data Analysis

Extra Benefits-

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

Who Should Enroll?

• For this specialization program, there is no prior knowledge required. Anyone can enroll in this program, who wants to learn SQL.

Interested to Enroll?

If yes, then check out all details here- Learn SQL Basics for Data Science Specialization

27. R Programming – Coursera

Rating- 4.5/5

Provider- Johns Hopkins University

Time to Complete- 58 hours

This course will cover all the basics of R Programming. If you want to learn R from scratch, then this course is for you. In this course, you will learn how to program in R and how to use R for effective data analysis. This course will teach you programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting on R code.

Now, let’s see the topics covered in this course-

1. Installing R
2. Overview and History of R
3. R Console Input and Evaluation
4. Data Types
5. Subsetting
6. Vectorized Operations
7. Introduction to swirl
8. Control Structures
9. Functions 
10. Scoping Rules
11. Loop Functions
12. Debugging Tools
13. Simulation
14. R Profiler

Extra Benefits-

• You will earn a Shareable Certificate.

Enroll in this course if-

• You have a basic knowledge of regression.
• If you want to learn only the Basics of R Programming.

Interested to Enroll?

If yes, then check out all details here- R Programming

28. Python for Everybody  – Coursera

Rating– 4.8/5

Provider– University of Michigan

Time to Complete- 8 months

This is one of the most popular and highly enrolled Specialization Programs. 1.7 M students have enrolled in this specialization program. This specialization program will teach you fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language.

Along with that, you will build your own applications for data retrieval, processing, and visualization. This specialization program consists of 5 Courses.

NOTE- You can also enroll for any single course within these 5 courses. And after completing the course and hands-on project, you will get a certificate. But completing the full program is beneficial for you.

Skills Gain-

1. JSON
2. XML
3. Python Programming
4. Database (DBMS)
5. Python Syntax And Semantics
6. Basic Programming Language
7. Computer Programming
8. Data Structure
9. Tuple
10. Web Scraping
11. Sqlite
12. SQL

Extra Benefits-

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

Now, let’s see whether you should enroll in this certification course or not?

Who Should Enroll?

• Anyone can enroll in this specialization program. Someone with no programming experience can also enroll in this program.

Interested to Enroll?

If yes, then check out all details here-  Python for Everybody 

So, these are the other best data science course for specific skills in the “Best Online Data Science Courses List”. Now, let’s see the step-by-step Data Science Roadmap with Python Programming-

Data Science Roadmap and Essential Skills

A data scientist requires an in-depth knowledge of the following skills-

1. Programming Skills
2. Statistics or Probability
3. Machine Learning
4. Multivariate Calculus and Linear Algebra
5. Data wrangling.
6. Data Visualization.
7. Database Management
8. BigData

Step 1- Learn Python First

If you are a complete beginner and don’t have Python Programming knowledge, then first learn Python

Step 2- Learn Math & Statistics

To learn data science, you should have a good understanding of Statistics and mathematics.

Step 3- Familiar with Python Libraries

Now, you need to know how to deal with data. And for this, Python has a rich set of libraries to perform data manipulation, analysis, and visualization.

Step 4- Brush Up on SQL Skills

You should know how to store and manage your data in a database. That’s why you should have an understanding of SQL.

Step 5- Learn Machine Learning Algorithms

At this step, you need to learn the basics of Machine Learning and the Types of Machine Learning algorithms( Supervised, Unsupervised, Semi-Supervised, Reinforcement Learning).

Step 6- Build Your First Machine Learning Model with scikit-learn

Now, you know how to perform data manipulation, analysis, and visualization. It’s time to predict something and find interesting patterns from the data. 

Step 7- Take Part in Data Science Competitions

Now it’s time to practice and check your command in Data Science. The best way to practice is to take part in competitions.

For a more detailed Data Science Roadmap, check this article- Data Science with Python Roadmap from Scratch

As a Data Science learner, you might have a question-“What is the Best Programming Language for Data Science?”. So, let’s see the best programming language for data science-

Best Programming Language for Data Science

To answer this question, I will compare the three most used programming languages for Data Science- Python, R, and Julia.

Python vs R vs Julia

Criteria	Python	R	Julia
Usage-	Python is a general-purpose programming language.	R is used for Data Analysis, Statistical Analysis, and Data Visualization.	Julia is used for Scientific computing.
Speed and Performance–	Python has average speed and performance.	R is a slow programming language.	Julia has high speed and performance similar to C language. Due to its high speed, there are approximately 13M downloads happening till May 2020.
Community-	Python has a huge community. That means, there is a huge Python community that can help you when you are stuck at some point.	R has also a huge community but not huge as Python.	Julia has a small community because it’s a new language. It might take 3 to 4 years to build a huge community.
Libraries available	Python has more than 200k libraries. This is quite huge.	R has approximately 15000 libraries.	Julia has approximately 3000 libraries.

So, this is the basic comparison between Python, R, and Julia. But the final conclusion has still not been drawn. For that, I will answer this question-

When to use Julia?

As I mentioned earlier, Julia has high speed and performance. So, If you have a huge data set, and you want a faster result, then only you should use Julia.

The next question that may come to your mind is, “Should I learn Julia or not?

The answer to this question depends upon your experience level. So I will explain both cases-

For Experienced-

If you are an experienced person, that means you have enough knowledge of Python or R. And you have done various data science tasks in Python or R, then you can learn Julia in order to enhance your skills. Knowledge of Julia will give you more privilege as a data scientist.

For Freshers-

If you are fresher and planning to start your career as a Data Scientist, then you shouldn’t start with Julia. For freshers, it is better to start with Python. Once you are familiar with Python and perform some data science projects in Python, then you can learn Julia.

Now, you got a clear answer for both cases. The next question is, “Python or R, Which should I use for Data Science?”

Python or R

If you are a beginner then the answer is Python. Why?. because Python is easy to understand language. You can perform all data science tasks easily with the help of Python. That means, starting your data science journey with Python.

As a fresher, you should have knowledge of only two programming languages- Python and SQL. That is enough for you. Once you cleared this level, then you can learn any other language.

If you are an experienced person, then knowledge of both (R and Python) is beneficial for you. Becoming an expert requires constant learning. The more knowledge you have, the more options you can create for yourself.

I hope, now you got an answer to all your questions. 

Now, you might have a question, “Which MOOC Platform is Best for Data Science?”.

Which MOOC Platform is Best for Data Science?

Let’s have a quick comparison between Coursera, edX, Udacity, Udemy, and DataCamp-

	Coursera	edX	Udacity	Udemy	DataCamp
Price	$39/month	Free to Audit, but for full material and certificate it cost around $50 to $300.	$399/month.	$10 to $199	Free account ($0), the Standard ($25 a month), or the Premium ($33.25 a month)
Mode of Learning	Self-paced videos with scheduled learning	A mix of self-paced or instructor-paced classes.	Most of the Udacity courses are self-paced.	Self-paced videos	Self-paced videos
Languages	Many Languages	English	Mostly English	Wide range of languages	English
Certificate Accreditation	Accredited certificates	Accredited certificates	Not Accredited	Not Accredited	Not Accredited
Course structure	Video Lectures, Quizzes, and assignments	Short videos, interactive learning exercises	Nanodegree programs and Free Online Courses	Video lectures	Video lectures
Best For-	Those who are looking for more detailed, structured, and credible courses from Top Universities.	Anyone who is looking to earn accredited certificates or university degrees.	Those who are looking for more real-world project-based advanced data science training.	Those who are looking for short courses that provide enough information in a short amount of time.	DataCamp is for those who are new in the field of Data Science and want to learn the basics of Data Science.
	Free Sign Up at Coursera	Free Sign Up at edX	Free Sign Up at Udacity	Free Sign Up at Udemy	Free Sign Up at DataCamp

So, you can choose the platform according to your preference.

That’s all for Best Online Data Science Courses.

Now, it’s time to wrap up this Best Online Data Science Courses article.

I hope these 28 Best Online Data Science Courses will help you to learn Data Science. 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 28 Best Online Data Science Courses. If you have any doubts or questions regarding these Best Online Data Science Courses, feel free to ask me in the comment section.

Thank YOU!

Explore More about Data Science, Visit Here

Though of the Day…

‘ It’s what you learn after you know it all that counts.’

– John Wooden