We’ve gathered the 9 Best Data Science Course on Coursera to help you kickstart or advance your learning journey online. And guess what? You can try any of these Data Science Specialization courses for free for 7 days!
That’s right! Coursera offers a 7-day free trial on these specialization courses, which gives you a great opportunity to explore the course content before committing to a subscription. We’ve also mentioned some of the best Data Science courses on the edX platform as alternatives, so you’re fully covered.
Every Data Science course on Coursera is carefully designed to equip you with the skills you need for a successful career in this field. We’ve handpicked only the best, so you can make your choice confidently.
In a Hurry?
If you’re short on time, here are quick links to some of the top picks for Data Science on Coursera. We’ve only recommended the best resources for learning Data Science:
–Introduction to Data Science Specialization is suitable if you’re looking to learn basic topics.
–IBM Data Science Professional Certificate is the one you should consider for career enhancement.
–Data Science using R Specialization is good if you would like to learn Data Science with R.
–Applied Data Science with Python by the University of Michigan is another popular alternative.
Now, let’s proceed to find the best Coursera courses for Data Science.
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Best Data Science Course on Coursera
Data science courses are essential for building the skills needed to become a proficient data scientist. These courses offer a well-structured curriculum designed to provide in-depth knowledge of the field.
With numerous online and offline courses available, each focusing on different aspects of data science, deciding what should be included in a comprehensive Data Science curriculum can be challenging. Different educational philosophies influence course content and structure.
Data Science course curricula generally follow one of three approaches: breadth-first, depth-first, or a combination of both.
1. Introduction to Data Science Specialization
IBM offers this beginner-level Data Science course on Coursera, designed to help learners build a strong foundation in Data Science from the ground up. This specialization is ideal for individuals looking to start learning Data Science from scratch. The course content focuses on developing essential skills before advancing to more complex topics, making it a suitable starting point for beginners.
The course begins with an overview of the history and basic terminology of Data Science. Participants will then learn about key areas within Data Science, including statistics, machine learning, and data mining, along with their real-world applications.
This course caters to those new to Data Science, as well as professionals looking to refresh their skills. It is suitable for a diverse audience, including data analysts, scientists, marketers, business professionals, educators, and students.
Key takeaways of the course:
- Gain insights from experienced Data Science practitioners through overview sessions.
- Learn popular Data Science tools and how to use them effectively.
- Understand methods for solving Data Science challenges.
- Develop SQL skills for extracting data from databases.
- Receive graded materials and a shareable professional certificate upon course completion.
More than 37k students have taken this course to learn the basics of Data Science from Coursera. The time to complete this specialization is about 4 months.
2. IBM Data Science Professional Certificate
Compared to the previous IBM’s Introduction to Data Science, this has few overlap courses. Because this course features the most detailed and comprehensive Data Science curriculum. It features 9 courses to build job-ready skills. According to the data from Coursera, 46% of the students started a new career after completing this specialization. And 19% of them either got a raise in pay or promotion.
To enroll in this Data Science course, there are no prerequisites. But, it would help if you’ve some math skills like Calculus and Linear Algebra. The skills that you develop while taking this course are SQL, Python, Data Analysis, Data Visualization, and ML. The advantage of completing this course is that you get a digital badge from IBM as well. This will make your resume and portfolio stand out from the rest.
Key takeaways of the course:
- You will learn about the best tool in Data Science, IBM Watson.
- Study various tools and their features and how to use it to solve complex problems.
- Learn the popular Python modules, such as NumPy and Pandas.
- You will create a database instance in the cloud to practice SQL queries.
- The essential skill to learn is Data Visualization using Python to represent any data to be readable.
- Includes several practice labs and projects to prepare you with job-ready skills.
This is one of the best Data Science course on Coursera to take online. More than 190k students have signed up for this course to develop skills in Data Science. We’ve written a detailed review of the IBM Data Science Professional Certificate.
3. Data Science: Foundations using R Specialization
John Hopkins created the Data Science Foundations using the R language. R language is another alternative to Python to master Data Science. To enroll in this course, you should have programming experience in any language. Also, it helps if you have some knowledge of mathematics up to algebra. This specialization comes with 5 courses that teach the basics of Data Science using R programming.
Here you’ll learn how to start programming in R and how to clean, explore data, and conduct reproducible research. . You’ll also learn how to manage a project and its associated files. The first step in learning R is downloading and installing the software. Each course in this specialization ends with a hands-on practice lab to enhance your learning. Once you complete this foundation course, you can sign up for advanced Data Science: Statistics and Machine Learning Specialization.
Key takeaways of the course:
- This course is suitable for those looking to use the R language in solving Data Science problems.
- Using the R language, you’ll clean, analyze, and visualize data.
- Efficiently manage your Data Science projects using GitHub.
- Asking the right question will get you the right answer. This course teaches you to ask the right questions.
- Learn to set up R, R-Studio, Github, and other useful tools.
- Create data graphics using plotting systems in the R language.
The foundations of Data Science using R will take you 6 months to complete the course. Once you complete this course, take the advanced course to complete your training.
4. Data Science: Statistics and Machine Learning Specialization
This course should only be taken if you’ve completed the previous course Data Science Foundations using R. As the foundational course, this too features 5 courses in this specialization. Every topic is covered by a practical approach to getting things done. This is an advanced course using R language that covers regression models, statistical inference, and ML.
Every course in this Data Science specialization comes with hands-on labs and peer-graded assignments. Once you complete four of the five courses, you will reach the fifth and final course. The final capstone project should be completed to earn a professional certificate.
Key takeaways of the course:
- This is an advanced course using the R language in Data Science in Coursera.
- Using regression models, you learn how to perform inference, regression analysis, and least squares.
- You’ll learn to develop, build, and apply prediction functions.
- It provides basic lectures on concepts of overfitting, error rates, training, and test sets.
- Tell a story using data that was created using statistical fundamentals of creating a data product.
This advanced course in Data Science using R will take another 6 months to complete.
5. Data Science Specialization by John Hopkins
This specialization course is the combination of the 3rd and 4th courses mentioned in this post. If you’d like to take both the foundation and advanced course in a single certification, it is the right one. Data Science Specialization by John Hopkins teaches Data Science using R programming. R is another great alternative to Python in Data Science.
The industry partners of this specialization are Swiftkey and Yelp. The projects involve real-world data. By completing more Data Science projects, you’ll have many things to update on your resume and portfolio. For more hands-on labs, refer to the best Data Science projects for beginners for practice.
Key takeaways of the course:
- A single course containing both basic and advanced topics of Data Science using R.
- Comprehensive 10-courses developed and taught by leading professors.
- Self-paced online training with several hands-on labs and graded assignments.
- A final capstone project that uses all the skills you learned throughout the ten courses.
This Data Science specialization course by Coursera is enrolled by more than 300k students.
6. Applied Data Science with Python Specialization
The University of Michigan has developed this best Applied Data Science course on Coursera. The students will learn Data Science using Python language. This specialization course is carefully curated with 5 courses to cover length and breadth to make you Data Scientist. If you’ve basics Python programming knowledge, then this course is for you. 36% of the students who took this course have started a new career.
Here you will learn how to put Data Science techniques and methods and gain analysis skills. Popular Python libraries such as matplotlib, pandas, and scikit-learn are taught using practical labs. Using Python, you’ll also apply many popular methods to solve the complex problems of modern Data Science. You can read the complete Data Science with Python review.
Key takeaways of the course:
- Using the Python pandas, you will master data manipulation and cleaning techniques.
- Visualization basics are taught here to students using Python. And recognize whether a data visualization is good or bad.
- You will be able to conduct an inferential statistical analysis.
- Using applied Machine Learning, you will enhance data analysis in Data Science.
- By the end, students can differentiate between the supervised (classification) and unsupervised (clustering) techniques.
This intermediate Applied Data Science course can be completed in 5 months. Over 200k learners have enrolled in this course.
7. Advanced Data Science with IBM Specialization
To further enhance the knowledge of the current Data Scientist, IBM has designed this advanced course. IBM’s Advanced Data Science specialization course by Coursera is designed to train you in Deep Learning and ML. A basic understanding of Machine Learning would be a plus point, but Python is recommended. IBM instructors train you in Data Science by providing practical examples of the real world.
With this course, you become an IBM-approved Expert in Data Science, ML, and AI. By taking this class, the maths used in ML and Deep Learning algorithms will become easier. Along with Certification from Coursera, you will receive a digital badge from IBM. The skills of data structures and algorithms will have a significant advantage in writing efficient codes.
Key takeaways of the course:
- It covers a brief overview of maths, Python, and SQL.
- Learn how the basic statistical measures are used to reveal patterns within the data.
- By using advanced tools and charting libraries, you will improve the efficiency of analysis.
- An advanced level Data Science course on Coursera with flexible deadlines.
- Use a wide range of frameworks and technologies.
More than 26k students have signed up for this course, and about 67% have started a new career.
8. IBM Applied Data Science Specialization
IBM’s Applied Data Science course can be taken even if you’ve no prior experience in either programming or Data Science. But some basics of Data Science knowledge wouldn’t hurt. In this course, you will gain the practical skills to solve real-world data problems.
The necessary Python programming is taught in this course from the ground up. Data visualization and data analysis are also taught here, which are both crucial and essential for Data Science. This beginner’s course will pave the path for advanced IT skills such as AI, Deep Learning, and Big Data.
Key takeaways of the course:
- It starts by teaching you Python programming to take you from zero to programming.
- Using Python, learn how you can analyze data to perform simple statistical analysis, and create meaningful data visualizations.
- Learn to prepare a good visualization to present that data in a form that makes sense to people.
- It includes the final Capstone project that you should complete to get a certificate.
You need 5 months to complete this beginner’s Applied Data Science course. More than 29k learners have signed up for this course.
9. Executive Data Science Specialization
This course is a crash course on Data Science in Coursera by Johns Hopkins University. It is aimed at executive leaders, managers, and business leaders to make you conversant in Data Science. This specialization is composed of 4 courses that will teach you Data Science. So that you’ll recruit, gather, and create a team with the necessary skillset.
Here you will learn the structure of the Data Science pipeline and keep your team on target. Also, you learn to get trained to overcome some common challenges with practical skills.
Key takeaways of the course:
- You will be able to converse in the Data Science field.
- Understand the goals of the project in each stage to keep your team on target.
- Learn how you can navigate the structure of the data science pipeline.
- Overcome the common challenges that derail data science projects.
In two months, you can complete this specialization and earn the certificate. You can update your resume and portfolio with new skills learned in this course.
Summary: Best Data Science Course in Coursera is Worth it?
Conclusion: Find the Best Data Science Course on Coursera for You
With these 9 best Data Science courses on Coursera, you can start learning data science from scratch or level up your current skills to advance your career. Whether you’re interested in Python, R, or want to explore specialized topics like Machine Learning or Data Visualization, there’s a course tailored to meet your needs.
Remember, all of these courses come with a 7-day free trial, so you can explore and see what suits you best before committing. Dive into one of these highly-rated courses today and take the first step toward becoming a data scientist!
We’ve also an alternative list of the best Data Science courses on the edX platform.
Happy learning, and good luck on your Data Science journey!
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