Best Data Science Courses on Coursera

Find out which Coursera course is best suited for you this year

6 min readMay 17, 2021

When it comes to picking the best Data Science course from Coursera, one’s mind can be confused over the available options. Today, in this blog, I’ll share the top and the best Data Science courses that you can opt for on Coursera, based on your current knowledge and experience.

Coursera is an American open online course provider company. Founded in 2012 by Stanford University computer science professors Andrew Ng and Daphne Koller, Coursera works with universities and other organizations to offer online courses, certifications, and degrees in a variety of subjects.

Before we begin, I want you to know that there are mainly two kinds of courses available on Coursera.

Certificate Course — These are the courses for which you earn a specialization or a professional certificate upon successful completion. They should not be considered the same as a degree certificate.
Degree Course — These are the courses that earn you a proper degree (Bachelor’s/Master’s) upon successful completion. The degree that you earn here is generally equivalent to the one earned on the university campus.

In this blog, I’ll only be sharing the Certificate Courses that can help you learn Data Science online.

Certificate Courses

IBM Data Science Professional Certificate

This is a great course by IBM for beginners who want to learn everything end to end. You will begin to learn things like what Data Science is, what Data Scientists do, the various tools they use, and the methods they apply.

You will also gain hands-on knowledge on:

Importing & cleaning datasets
Analyze & visualize data
Build machine learning models
Evaluate pipelines using Python.

In the end, you will be able to apply various data science skills, techniques, and tools to complete a project.

Approximate Course Duration 
11 months (At suggested pace of 4 hours/week)Perks
Shareable Cerificate and digital IBM badge recognizing your proficiency in Data SciencePrerequisites
No prior experience requiredRating
4.6 / 5 (Rated by more than 46,000 people)

Google Data Analytics Professional Certificate

In March 2021, Google launched its course of Data Analytics which caught the attention of quite many aspiring people. This course by Google covers everything one needs to know to get an entry-level job as a Junior Data Analyst.

You will learn key analytical skills (data cleaning, analysis, & visualization) and tools (spreadsheets, SQL, R programming, Tableau), understand how to clean and organize data for analysis, and how to visualize and present data findings in dashboards, presentations, and commonly used visualization platforms. These truly are the most sought skills by recruiters when it comes to hiring junior-level Data Analysts.

Apart from the certificate, upon successful completion of this course, you will gain access to an exclusive job platform where you can easily apply to opportunities from employers with open jobs.

Approximate Course Duration 
6 months (At suggested pace of 10 hours/week)Perks
Shareable Cerificate and access to an exclusive job platformPrerequisites
No prior experience or degree requiredRating
4.8 / 5 (Rated by more than 7,500 people)

Machine Learning Specialization (Offerred by DeepLearning.Ai)

This Machine Learning Specialization by DeepLearning.Ai and Stanford is another decent and highly rated course by Coursera. It’s a beginner-friendly course that covers the fundamentals of machine learning and how to use ML techniques to build real-world AI applications.

This course offers a comprehensive overview of contemporary machine learning techniques, encompassing supervised learning (such as neural networks, multiple linear regression, logistic regression, and decision trees), unsupervised learning (like clustering, dimensionality reduction, and recommender systems), and commonly employed strategies in Silicon Valley for developing artificial intelligence and machine learning (such as optimizing and adjusting models, adopting a data-focused methodology for enhancing performance, and other methods).

Approximate Course Duration 
3 months (At suggested pace of 9 hours/week)Perks
Shareable CerificatePrerequisites
Beginner level experience in PythonRating
4.9 / 5 (Rated by more than 10,000 people)

Deep Learning Specialization (Offered by DeepLearning.Ai)

Now if you already have some sense of what Machine Learning is, and you are also equipped with intermediate Python skills (basic programming, understanding of for loops, if/else statements, data structures, etc.), then this is an excellent course for you.

This is an advanced course with which you can:

Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and deep learning to applications.
Train test sets, analyze variance for DL applications, use standard techniques and optimization algorithms, and build neural networks in TensorFlow.
Build a CNN (Convolution Neural Network) and apply it to detection and recognition tasks, use neural style transfer to generate art, and apply algorithms to image and video data.
Build and train RNNs (Recurrent Neural Networks), work with NLP (Natural Language Processing) and Word Embeddings, and use HuggingFace tokenizers and transformer models to perform NER and Question Answering.

This course is not ideal for complete beginners but is very good for those who want to advance their careers in Deep Learning and Artificial Intelligence. One of the instructors of this course is Andrew Ng, a renowned expert in Deep Learning and one of the co-founders of Coursera and DeepLearning.Ai.

Approximate Course Duration 
5 months (At suggested pace of 7 hours/week)Perks
Shareable CerificatePrerequisites
- Intermediate Python skills
- A basic grasp of linear algebra & MLRating
4.5 / 5 (Rated by more than 36,000 people)

Data Science Fundamentals with Python and SQL Specialization (by IBM)

This course by IBM is yet another beginner-friendly course, which allows you to learn data science without having to have any prior knowledge of Computer Science or even programming. Yes, that's right. It will cover the programming fundamentals as well as the tools needed for Data Science.

I recommend this course highly to those who are from a non-technical background and are willing to switch their career to Data Science.

You will get to learn the following set of skills:

Working knowledge of Data Science Tools such as Jupyter Notebooks, R Studio, GitHub, Watson Studio.
Python programming basics including data structures, logic, working with files, invoking APIs, and libraries such as Pandas and Numpy.
Statistical Analysis techniques including Descriptive Statistics, Data Visualization, Probability Distribution, Hypothesis Testing, and Regression.
Relational Database fundamentals including SQL query language, Select statements, sorting & filtering, database functions, accessing multiple tables.

Approximate Course Duration 
6 months (At suggested pace of 3 hours/week)Perks
Shareable CerificatePrerequisites
Basic computer literacyRating
4.5 / 5 (Rated by more than 36,000 people)

These are my top picks for you. I hope this helps you decide the best Data Science course for yourself. You can always look for more courses on Coursera at this link .

In my upcoming blog, I’ll also cover the best Degree Courses for Data Science on Coursera. Stay tuned. Happy Learning.