Best Data Science Courses Online in 2024

Data science involves collecting, organizing, and analyzing data to extract valuable insights. This process utilizes programming, Artificial Intelligence, Machine Learning, and analytical skills. According to Technavio, the global Data Science market is expected to grow at a CAGR of 26.78% in the coming 5 years. The growth of the Data Science industry is driven by the increase in data generation by almost all industries – healthcare, retail, BFSI, etc. This is reflected in the number of job opportunities and the salaries. The average salary of a Data Scientist is USD 123,698.

Almost every organisation depends on data science for improved decision-making that, in turn, helps increase profits. Data science is applicable in handling various types of datasets in different organisations, opening up different roles for data science graduates. These job roles include data analyst, data scientist, business analyst, data engineer, statistician, data architect, and many more.

With hundreds of platforms and options online, it can be a little challenging to choose an online data science course that aligns with one’s requirements. In this article, I am reviewing the 10 best data science courses online across different platforms, such as Udemy, Coursera, and LinkedIn Learning. It includes key course details to help you choose a relevant course. Check: Best Data Science Courses on Udemy

1. The Data Science Course: Complete Data Science Bootcamp 2024

The Complete Data Science Bootcamp course is created by 365Careers. They are one of the top Udemy instructors/creators. If you are a beginner and you need to revise basic Mathematical and Statistical concepts before you want to move to Data Science, this course is ideal for you. The course starts from the basic concepts of Maths and Statistics and gradually moves towards Machine Learning and Deep Learning with TensorFlow.

Like any other Udemy course, this course also focuses on hands-on learning. I worked on real-life business cases. I am now able to analyze data as well as effectively communicate insights to the stakeholders.

• Platform: Udemy
• Ideal For: This course is ideal for beginners. I would recommend this course to college students who want to explore the Data Science field and figure out if they want to make a career in it.
• Course Duration: 31 hours
• Does this Course Focus on Practical Learning: Yes, the course includes 138 coding exercises and real-life business cases. 

2. Intro to Data Science: QuickStart Guide + AI & ChatGPT Prize

The Intro to Data Science course claims to teach you all the skills needed to become a data scientist in just 6 weeks. Kirill Eremenko is the instructor of this course. He is a Data Scientist and was trained by the lead analysts at Deloitte, Australia. This was enough to trust what the course had to offer. The course focuses on practical skills, stripping away unnecessary content to provide a structured learning experience.

I learned how to use tools like SQL, Tableau and Python by working on real-world examples. The course focuses more on the applications of Machine Learning algorithms with Python and statistical proficiency.

• Platform: Udemy
• Ideal For: I’d suggest this course for anyone wanting to understand how to become a data scientist. If you’re just starting, it’s a great way to learn about the skills and requirements for the role. However, keep in mind that to learn even the basics, you might need to take more courses.
• Course Duration: 5 hours
• Does this Course Focus on Practical Learning: Nope, it doesn’t have practical examples and real-life case studies. They sort of just explain how tools like SQL and Tableau work.

3. Foundations of Data Science

Foundations of Data Science course is a part of the ‘Google Advanced Data Analytics Professional Certificate’, both are available on Coursera. The course can teach you the skills needed for advanced data professional roles such as data scientist or lead data analyst. The course talks about project workflow PACE (Plan, Analyze, Construct, Execute) and how it can help you organize the data projects. I would not recommend this course to beginners. It is suitable for data analysts or data-related professionals in their early careers who want to move into lead roles. The course assumes you have the basic knowledge of analytical principles, skills, and tools used in data analytics.

• Platform: Coursera
• Ideal For: The course is suitable for data analysts or data-related professionals in their early careers who want to move into lead data scientist or data analyst roles.
• Course Duration: 26 hours
• Does this Course Focus on Practical Learning: No, it focuses more on soft skills and PACE analysis activity. There are some assignments and quizzes but they also test your knowledge about the soft skills and the basics of data science.

4. Data Science Methodology

The course claims to teach you the shortcuts to become a data scientist i.e. to think and work like a successful data scientist. You’ll learn and apply two important data science methodologies, the foundational data science methodology, and the six-stage CRISP-DM data science methodology. These are the approaches many experienced data scientists use for solving problems. The course guides you through forming a business or research problem, obtaining, preparing, and analyzing data, and proper manipulation. You’ll also dive into building data models, deploying them, engaging in data storytelling, and getting feedback. The hands-on experience in Jupyter Notebooks using Python helps you develop your data science methodology skills in a real-world scenario.

• Platform: Coursera 
• Ideal For: The course is ideal for aspiring data scientists looking to fast-track their careers by learning the shortcuts and methodologies used by experienced data scientists.
• Course Duration: 6 hours
• Does this Course Focus on Practical Learning: Yes, the course focuses on teaching through real-world scenarios using Jupyter Notebooks and Python to develop data science skills.

5. Data Science Foundations

Barton Poulson, the instructor of this course, breaks down the complicated topics in an easy-to-understand manner. What I like the most about this course, and probably the one thing that makes it different from other data science courses is the fact that it covers the basics, tools, and techniques and then connects data science with other fields like machine learning and artificial intelligence. Poulson also delves into ethics and accountability, to cover the soft skills portion. 

• Platform: LinkedIn Learning 
• Ideal For: The course covers the basics of data science so I believe it would be a good starting point for the students wishing to learn about the data science field.
• Course Duration: 5 hours 17 minutes
• Does this Course Focus on Practical Learning: Not really, the course does contain 10 quizzes to test your knowledge but they are meant to assess your theoretical knowledge only.

6. Learning Data Science

I want to include this course in the list of my 10 best data science courses available online because it is meant for people who aren’t aiming to be full-time data scientists but want to explore the potential of data science for business value. Doug Rose, the instructor of the course, breaks down big data concepts, tools, and techniques in an easy-to-understand manner. From sorting data to statistical analysis, he helps us speak the language of data science. If you are an associate or manager working with the data science teams, you will be aware of all the data-related concepts from now on.

• Platform: LinkedIn Learning 
• Ideal For: The course is ideal for managers or associates who work closely with the data team and just want to learn the basics of data science.
• Course Duration: 1 hour 16 minutes
• Does this Course Focus on Practical Learning: Not really, the course does contain quizzes to test your knowledge but they are meant to assess your theoretical knowledge only.

7. Professional Certificate in Data Science – edX

This course helped me learn fundamental R programming skills, understand statistical concepts like probability and inference, and apply them in real-world scenarios. I also gained hands-on experience with tidyverse, mastering data visualization and wrangling using dplyr. Throughout the course, I became familiar with crucial tools for data scientists such as Unix/Linux, git, GitHub, and RStudio. Now, I feel confident implementing machine learning algorithms and have a solid understanding of key data science concepts. 

• Platform: edX
• Ideal For: The course is ideal for those who want to learn R programming, statistics for data science, and practical experience with tools like tidyverse.
• Course Duration: 1 hour 16 minutes
• Does this Course Focus on Practical Learning: Yes, the course offers hands-on experience with tools such as tidyverse, Unix/Linux, git, GitHub, and RStudio.

8. Data Science: Data-Driven Decision Making

The course focuses on the ins and outs of tidying, harvesting, and wrangling data, along with applying statistical models to simulate complex functions. I learned how to develop effective data visualization for decision-making. The course also includes a section that explores the ethical, legal, and organizational aspects of data collection. Overall, it equipped me with the skills essential for a data scientist.

• Platform: FutureLearn
• Ideal For: The course is ideal for entry-level data scientists or students studying data science but looking for resources to learn processes like tidying, harvesting, and wrangling data, as well as applying statistical models for complex functions.
• Does this Course Focus on Practical Learning: Yes, the course helped me develop an effective data visualization model for decision-making.

9. Data Science for Business Leaders

As the name suggests, this course on data science focuses on the business aspect. The course has lessons on strategic business objectives, understanding the human capital aspect of data science, and crafting a solid data and data architecture strategy. The hands-on capstone project is a highlight, where I made a 100-day data science plan for a chosen company. 

• Platform: Udacity
• Ideal For: I would recommend this course to data scientists in their early careers who eventually want to move into advanced roles.
• Duration: 4 weeks
• Does this Course Focus on Practical Learning: Yes, the course includes a capstone project that involves preparing a 100-day data science plan for a company of my choice.

10. Introduction to Data Science

The course ‘Introduction to Data Science’ is a beginner-level course offered by Udacity. In this course, you will learn the data science process, including how to build effective data visualizations and how to communicate with various stakeholders. You will gain skills such as predictive analytics, data storytelling, exploratory data analysis, Github portfolios, etc.

• Platform: Udacity
• Ideal For: I would recommend this course to college students or beginners to want to learn the basics of data science.
• Duration: 3 weeks
• Does this Course Focus on Practical Learning: Yes, the course includes a project in which you will create a blog post and Github repository that you can use as you build your data science portfolio.