Best Data Science Courses Available


Top 30 Best Data Science Courses Available in 2021


It’s been some time since data science took the world by storm and continues to top among best paying Computer Science jobs. Moreover, the low number of genuinely skilled data scientists is making the demand go even higher. However, this has opened new possibilities for many CS graduates who want to establish a successful career in computer science. Given you enroll in the right data science courses and are determined enough to get through them, you too can bag a lucrative data scientist position in even the biggest corporations. Below, we’ve prepared a list of 20 great data science programs to help you do so.

Best Data Science Courses You Can Take Right Now

Since many topics fall under the domain of data science, our experts tried their best to choose the best data science online course for the key topics. In no way, this guide assumes that you’ll learn every ins and outs of data science from just these courses. They are here merely to kickstart your journey into this fantastic field.

1. Machine Learning A-Z™: Hands-On Python & R In Data Science

Termed as the best data science online course by many, this is one of those courses you can not miss. Udemy offers this data science course that empowers students with a real-world data science scenario and provides powerful tools to delve even deeper into the field. This course’s hands-on approach helps beginners understand many of the underlying concepts and their usage in the industry.

Highlights of this course

  • It makes students implement various Machine Learning algorithms in Python and R, thus strengthening their programming language skills.
  • Apart from making pristine predictions, students will also learn advanced data science techniques such as dimensionality reduction from this data science training.
  • The powerful Machine Learning models that students will learn from this program will solidify their data science knowledge to a new level.

2. Python for Data Science and Machine Learning Bootcamp

The pinnacle of modern data science courses, this course deals with many tools, including NumPy, Pandas, Seaborn, Matplotlib, Scikit-Learn, and Tensorflow, to increase your data science skills at a practical level. Taken by over two hundred thousand students worldwide, this is among those data analytics courses that introduce students to powerful big data analysis techniques in real-time.

Highlights of this course

  • It helps students learn and master the ins and outs of data science tools used heavily in the industry.
  • This course leverages the Python programming language for analyzing business data.
  • It deals with advanced Machine Learning techniques like Regression, Random Forest and Decision Trees, Neural Networks, Natural Language Processing, and Support Vector Machines.
  • This course also helps the students master data analytics algorithms that are incorporated into professional business solutions.

3. Data Science A-Z™: Real-Life Data Science Exercises Included

If looking for robust data science programs that will enable you to learn real-world data analytics, then this course is here for you. As the name of the course suggests, it deals with all the essential things you need to know about big data training in a merely 21 hours long course. You’ll learn precisely how real-world data science problems arise and are handled from this carefully designed course.

Highlights of this course

  • It analyzes complex data science problems with examples so that students can learn by doing things.
  • This powerful data science training enables users to perform data mining in Tableau and creating basic Tableau visualizations.
  • It allows students to create data querying scripts in SQL and apply them in their own projects.
  • This big data training builds a strong base for real-world data science models.

4. Machine Learning, Data Science and Deep Learning with Python

This is a compelling data science online course that provides students with a hands-on approach to Data Science, ML, and Deep Learning. The 12-hour-long course is designed so that even students with little or no prior data science knowledge can take this course without any trouble. Overall, this is an excellent intro to data science’s fantastic world and makes learning this large field much easier for beginning data scientists.

Highlights of this course

  • This course helps students in leveraging the Python language for real-world data science problems.
  • It discusses the fundamentals of probability and statistics for futuristic data science solutions in a smart way.
  • This big data training course is one of the few that shows how to utilize the Apache Spark framework for Big Data.
  • This course also makes students build robust Neural Networks with Keras and Tensorflow.

5. R Programming A-Z™: R For Data Science With Real Exercises!

R is a widely-used programming language in the field of data analytics. A competitive insight into how R handles real-world data science problems is a must for people who want to excel in their data science career. This course focuses entirely on R for solving traditional and futuristic big data problems. It doesn’t dive too deep into the world of data science, though. Instead, it gives a basic idea of the core concepts and shows how R can overcome the problems.

Highlights of this course

  • It teaches all the mandatory R concepts you’ll use as a data scientist and familiarizes users with the R studio.
  • You’ll learn how to customize the R studio according to your preferences.
  • This course equips students with a working knowledge f statistical data analysis in R.

6. Data Science Specialization Offered by Coursera

This is one of the most compelling data science courses you can take right now that will take your big data analytics skills to a whole new dimension. It covers almost every fundamental concept you’ll need to handle practical Big data and discusses the tools required to process them and reaching a solution. Contrary to other data analytics courses, this will take much time to complete due to its massive content.

Highlights of this course

  • From data acquisition to modeling, you’ll learn the entirety of data science concepts from this course.
  • It will help users to master GitHub and use it for potential data science projects.
  • This course utilizes the R programming language to clean, analyze, and concisely visualizing data.
  • The hands-on project included in his course makes sure you understand the concepts clearly and independently solve complex real-world problems.

7. Data Science Essentials by Microsoft on edX

A part of Microsoft’s Professional Data Science Certification Program, this course offers a brief intro to the essential data science concepts. This course provides a powerful means of learning the fundamental data science principles and is prepared to meet the increasing demand for quality data scientists. It teaches the fundamental concepts of Data Science like data acquisition, preparation, exploration, and visualization in a realistic way.

Highlights of this course

  • This course provides students with the practical implementation skills required to work with Python and R.
  • The hands-on approach taken by this course is curated to fit real-world situations.
  • Students will be familiarized with the Microsoft Azure Machine Learning platform and the Azure Stack.
  • It discusses the usage of probability and statistics in data science from a practical perspective.

8. Intro to Machine Learning by Udacity

If among different data science sub-disciplines, you’re particularly interested in Machine Learning, then this course might worth your time. Offered by Udacity, this course provides a thorough knowledge of different Machine Learning principles and how they’re implemented in the business world. It’s a massively popular course on Machine Learning that offers real-life examples and makes sure the contents stay related to the industry.

Highlights of this course

  • Professionals teach it with vast experience in the field who make sure the contents are of really high-quality.
  • This Machine Learning online course teaches students the end-to-end process of investigating massive datasets with powerful ML tools.
  • Students will learn to evaluate the performance of their Machine Learning algorithms from this course.
  • This course is suited to data analytics experts who want a quick experience of various Machine Learning techniques.

9. Data Science Foundations

The epitome of top quality data science courses, this is a compelling package curated, especially for aspiring data scientists looking for rich contents with plenty of practical problems to play with. The course is aimed at beginners with little or no previous experience in Machine Learning. If you’re looking for a short but compelling machine learning course to supplement your existing data science skills, our experts highly recommend this course.

Highlights of this course

  • This beginner-friendly course lays out an adequate learning flow for aspiring data scientists.
  • The entire course is divided into three parts, each discussing a specific niche.
  • It introduces students to widely used data science tools such as Jupyter Notebooks, RStudio IDE, Apache Zeppelin, IBM Watson Studio, etc.
  • It presents the fundamental concepts of data science enthusiastically to students with little or no knowledge about the field.

10. Learn Data Science from DATAQUEST

This is arguably amongst the most innovative data science courses for modern data science students. Contrary to most popular data science programs, this course is presented interactively. Students need to complete the “mission” inside DATAQUEST’s synergistic web app for completing a particular course. The choice of topics is diverse, and core concepts are presented in a playful yet effective way.

Highlights of this course

  • The interactive web view encourages students to learn more about crucial concepts by forcing them to go more.
  • This data science online course teaches Python, R, SQL, data visualization, data analysis, and machine learning effectively.
  • DATAQUEST is trusted by corporations like UBER, Spotify, and Amazon plus institutions like HARVARD.
  • Students will be writing their own code while working with real-world data sets with this rewarding course.

11. Genomic Data Science Specialization on Coursera

If you’re particularly interested in Genomic Data Science, then this course will steer up your interest even more. This advanced data science course is offered by Johns Hopkins University and is available through Coursera. The whole specialization is broken down into eight different courses that each deal with some specific concepts and tools. Among such notable tools, the command line, Python, R, Bioconductor, and Galaxy is of particular significance.

Highlights of this course

  • The course is curated in a hands-on project manner, helping students master the data science principles they learn by practicing.
  • It discusses the most common algorithms used in DNA sequencing and helps students analyze them creatively.
  • The course also touches on statistical problems that arise in Genomic data science projects frequently and suggests ways to avoid them.
  • It helps students learn and master tools from the Bioconductor project to analyze Genomic data properly.

12. Introduction to Computational Thinking and Data Science

This is a great data science training course taught by MIT that equips students with real-world data scientist skills. Designed for people with little to no prior programming experience, it leverages Python to implement compulsory data science techniques. After completing this compelling course, you’ll have a strong understanding of the field’s core concepts and will be comfortable enough to take on real-life data science projects.

Highlights of this course

  • The course is designed cleverly and offers an excellent introduction to the field before delving deep into advanced principles.
  • Each of the five problem sets requires students to solve Python’s programming problems, thus strengthening their Python skills.
  • The required course materials, including slides, files, and videos, are freely available for download.
  • This course emphasizes practical problem solving rather than memorizing algorithms.

13. Big Data Integration and Processing by UC San Diego

It is one of the most compelling big data training programs to deal with Big Data analysis in-depth. Offered through Coursera, this modern-day data science training aims to provide students with the knowledge and tools required to analyze and process real business data. This is a beginner-friendly course that students can take with little or no past knowledge of big data analysis techniques.

Highlights of this course

  • This course walks the students through retrieving and storing big datasets from industrial data management systems.
  • It leverages the Hadoop and Apache Spark platforms to integrate and process big data.
  • Provides the necessary knowledge required to handle real-world big data problems feasibly.
  • The assignments are quite hard and require critical thinking to solve.

14. Introduction to Data Science Bootcamp by Metis

It is a rewarding data science online course that equips students with the essential data science skills required for tackling real-world, data-rich business problems. The entire program is curated productively and allows students to obtain principal data science skills by solving problems. It also discusses the basics of statistics and other mathematical foundations that are often utilized in practical data science problems.

Highlights of this course

  • It provides a clear understanding of data acquisition, cleansing, and aggregation in real-world contexts.
  • This course encourages students to explore different data analytics techniques and visualization principles.
  • The authors have explained even advanced topics concisely and straightforwardly, making many concepts more transparent.
  • Students will learn how to model big data for practical business solutions effectively from this course.

15. CS109 Data Science Course from HARVARD

The CS109 Data Science is one of those few data science courses that provide students with almost everything they need to take their data science ability professionally. The course is very detailed and covers a lot of data science principles in a single package. The core data science concepts discussed by this course include Probability, Distributions, Frequentist Statistics, Regression, Machine Learning, Bayesian Methods, Interactive Visualization, and many more!

Highlights of this course

  • All the lectures of this data science training program come with slides and high-quality videos with subtitles.
  • This course utilizes a plethora of data science tools, including Pandas, Python, Jupyter Notebook, VirtualBox, AWS, Spark, and MapReduce.
  • The source codes for each problem’s solution is hosted on Github for exploration by interested students.
  • Due to its opensource nature, the course and materials can be used by anyone anytime.

16. Harvard Professional Certificate in Data Science

This data science course is a blend of technical tools, machine learning, and real-life case studies. This is one of the top-rated courses on edX. This course includes Inference and Modeling, R Basics, Productivity Tools, Visualization, Probability, Wrangling, Linear Regression, Machine Learning, and also a capstone project that has to be submitted at the end of the project.

This course focuses on

  • This course discusses fundamental concepts such as regression, sampling, data wrangling, and visualization.
  • It covers all the necessary tools like file organization, version control, and Github to tackle the real-world data challenges.
  • You will learn Basic data visualization principles, R language, and ggplot2 are also taught in this course to visualize & analyze data.
  • You will be able to judge the data and predict its frequency using probability at the end of this course.

17. Statistics and Data Science on edX

One of the most modern-day data science courses that dive deeper into statistical analysis, this course from MITx is a real gem to aspiring data scientists due to its ability to empower students with practical data science skills. The course, due to its massive contents, is broken up into five different parts. It equips students with advanced knowledge of the field and shows them how to solve them at industrial levels.

Highlights of this course

  • The course covers a lot of ground, from fundamental uncertainty to advanced statistical models used for business solutions.
  • It helps the students master the different methods for harnessing and analyzing data in real-world scenarios.
  • This is among those few data analytics courses that discuss advanced statistical analysis techniques like statistical inference alongside fundamental concepts.
  • The course also provides an in-depth intro to various Machine Learning techniques, including Regression, Decision Trees, K Forests, SVM, and Bayesian Networks.

18. Microsoft Professional Program in Data Science

You might be interested in enrolling in this course offered by Microsoft. The best part of this course is that industry professionals and experts design all the contents and lectures. Although this course can guide you through establishing yourself in this field. It still lightens basic concepts and tools like Microsoft Excel to explore your data-rich problems and find a solution to fit in real life.

This course focuses on

  • You will be taught to use tools and programming languages to explore critical data problems, such as using Microsoft Excel, to find and extract information from the relational database.
  • You will also learn to use tools like PowerBi to establish a connection between the random sources of a dataset.
  • This course also focuses on using machine learning to solve real-world data science problems and establish big solutions for complex problems.
  • You will be learning to use structural methods to generate models and Transact SQL to interact with the database.

19. Learning From Data by Caltech

This is a noteworthy data science training course that not only offers a brief intro to common data science problems but provides powerful ideas to overcome them. The free course can be taken by anyone according to their personal schedule and will still prove to be a viable resource. Although friendly to beginners, this course assumes a little familiarity with basic probability, matrices, and calculus.

Highlights of this course

  • The course provides a concise description of the major data science and machine learning theories, algorithms, and applications.
  • It comes with a topic by topic video lectures to review the concepts on their own time.
  • The homework problems are quite hard to crack without proper critical thinking and assertions.
  • A final exam determines whether you were able to understand the fundamental concepts clearly.

20. Applied Data Science with Python Specialization

If you’re an aspiring data scientist looking for free yet content-rich data analytics courses, then we’d definitely recommend you check out this course. The course discusses innovative ways of solving real-life business problems that deal with large amounts of data and needs to be catered according to the industry’s diverse requirements. Offered by Michigan University, this is a noteworthy data science course that can cater to your increasing data science demands.

Highlights of this course

  • This course introduces the most critical data science concepts to students with real-world problems, which mostly involve the Python programming language.
  • The knowledge students acquire from this massive data science online course can be applied to statistical analysis, machine learning, information visualization, text analysis, and social network analysis.
  • It aims to enhance your data analysis skills by incorporating modern-day machine learning techniques and tools.

21. R Programming

R Programming is a specialized data science program offered by Johns Hopkins University and provides students with a detailed knowledge of the language. Contrary to its heavy usage in the data science field, the number of quality materials to learn is quite short when compared to languages like Python and SQL. This course aims to rid this problem and provide aspiring data scientists with a compelling platform for learning R.

Highlights of this course

  • You will learn how to install necessary programs and configure the programming environment with R in this course.
  • It covers a lot of ground, from basic R concepts to advanced usage of R in big data analytics.
  • Students will learn to debug R programs effectively from this programming course.
  • This course also teaches how to simulate business data in R and to profile them effectively.

22. Mastering Data Analysis in Excel

This is among the most popular data analytics courses that deal with analyzing large-scale business data in Excel. It allows students to design and implement realistic predictive models based on Excel data that can be used directly in real-world projects. The course also comes with all the data students require to complete and practice the course.

Highlights of this course

  • This is an excellent course for learning data analysis within a short period.
  • It equips enough Excel knowledge so that students can design their own data analysis models.
  • This is among those data science courses that feature advanced data analytics techniques like binary classification, regression, information theory, and entropy measures.

23. Introduction to Data Science

This introductory course is designed by, which is available on their website, and you can directly enroll from anywhere in the world. This course will guide you to the basics of data science as well as mathematical and statistical approaches to tackle real-life problems in business and education. It will lead you from beginner to advanced concepts throughout the course. If you want to understand the Data Science concepts better, then this is the course for you.

This course focuses on

  •  Identifying the problems that can be solved with data science and applying a statistical approach to process the data
  • Creating data model variation and using methods for verification. 
  • Creating a pipeline using dataset and analytics to make applications in any programming language like python. 
  • Advanced algorithms and supervised patterns to generate regression and classification using vector machines, decision trees, and random forest models.

24. Introduction to Probability and Data

Your data science expertise depends on how accurately you can predict the future where probability and statistics are used to examine samples. This course covers various sample methods to explore data using R studio. Lab exercises and a final project are also included in the course. This course is available on the coursera website and offered by Duke University.

This course focuses on

  • An in-depth analysis of probability and statistics using different sample methods includes numeric summary statistics and basic data visualization.
  • Helps to use supervised and unsupervised learning methods using labeled and unlabeled data-rich problems.
  • Presentation of data pipelines and evaluate the advanced models with cross-validation and bootstrapping.
  • It also shares knowledge on how you can generalize your models as simple as possible.

25. The Data Scientist’s Toolbox

In many cases, results generated after applying data science become useless due to the absence of proper tools to portray the outcome. This course focuses on using efficient tools that should be used as a data scientist and introduces turning data into actionable knowledge. This course is offered by John Hopkins University and available on coursera’s website.

This course focuses on

  • Installing and Using data scientist’s toolbox, including python, R studio, GitHub, and others.
  • You will get a practical overview of Machine Learning to produce reproducible research and regression models.
  • This course mainly focuses on various concepts from hypothesis generation to hypothesis testing and error estimating.
  • It also focuses on identifying data problems and finding the actions needed for the future outcome.

26. Data-Driven Decision-Making

This course is designed to learn techniques to deploy a data-centric approach in business cases. Which helps you to be ready for the future to succeed in the competitive world. Every business deals with a vast amount of data and needs to collect necessary information from the critical dataset. You need to complete only four weeks of classes to earn a data science certification degree.

This course focuses on

  • This course emphasizes data representation through different elements like charts, graphs, maps, and other data visualization tools to understand the relations between data, patterns, outliers, and trends.
  • You will get the chance to learn many frameworks to analyze data problems involved in Big Data.
  • You will learn to make decisions upon results and information extracted after implementing data science on a given dataset.
  • You will see how data science can help to grow any business and can make your life easy as an entrepreneur.

27. Deep Learning Certification

This in-depth learning course is offered by and specially designed for students who want to master their deep learning skills. You will learn to use machine learning to build neural networks. Besides, LSTM, Dropout, Adam, Convolutional networks, RNNs, BatchNorm, and Xavier initialization will be discussed throughout the course. In addition to this, examples of different case studies will be provided, which will help you know your ability in data science.

This course focuses on

  • If you want to explore AI and deep learning, this course will help you to specialize yourself.
  • It will teach you to use Xavier initialization, a process to eliminate data that are outliers like too small or too large. Alongside this, the batch norm will be prepared to improve AI’s speed, performance, and stability.
  • It discusses the techniques to visualize better or represent data like convolutional networks, a neural network category.
  • You will be able to use CNNs to get a beneficial result of image recognition and classification.

28. Data Scientist Learning Path for Beginners

This course will teach you to play with data using SQL and analyze the statistics with Python. You will learn all the tools that data scientists use. And most importantly, this course emphasizes visualization to represent data and results. This course will teach to build machine learning algorithms and improve the performance for a better outcome.

This course focuses on

  • You will learn the advanced techniques to talk with your database using SQL. SQL is helpful to play with your data and establish relationships to extract meaningful information.
  • This course talks about different libraries and packages of Python like Panda, Numpy, and so on.
  • You will be learning to store & manage your data by manipulating rows and columns using these frameworks.
  • You will be trained to think like a real programmer. This course also introduces the idea of machine learning and artificial intelligence, although it is designed for beginners.

29. Applied Data Science with Python Certification

This course is one of the best data science courses offering Python programming language and covers all the toolkit of Python like pandas, matplotlib, nltk, and networks. Besides, Charting, Applied Plotting, and Data Representation in Python, Applied Machine Learning in Python. Applied Text Mining and Social Network Analysis in Python will be covered as well. You will able to analyze social media networks to generate traffic and be efficient in digital marketing campaigns to increase profit in business.

This course focuses on

  • This course focuses on the fundamentals of Python programming language.
  • It is designed to teach you how to manipulate CSV or Excel files to build a relational database and the numpy library.
  • This course focuses on Data mining, text mining, and social media mining to experience real-life problems and find solutions.
  • You will learn to generate a visual representation of data and evaluating the performance or analyzing how good, or bad the actual presentation is.

30. The Open Source Data Science Masters

Clare Corthell designs this basic course of data analytics. Although this course is for beginners, it covers a wide range of simple and advanced machine learning and statistics concepts. It also discusses programming languages like R & Python. As simplicity is the core feature of this course, you can easily catch the technical points and understand complex concepts.

This course focuses on

  • You will learn advanced data science concepts like data munging or data wrangling, a useful feature to map your data into the desired format.
  • Besides, this course also covers concepts like data management & exploratory data analysis.
  • It enables students to find the main characteristics of data and other methods of visual representation. You will learn to predict the result for the future by analyzing your data set.
  • Resource sharing, alongside natural language processing with Python, MapReduce/Hadoop & Pig Script, will be taught in this data analytics course.

When deciding on what data science courses to take, you need to evaluate your requirements first. Since specialization courses usually take extra time to complete, students with prior knowledge should pursue short courses that focus on a particular topic. However, if you’re a complete beginner, we recommend taking your time and completing one or two specialization data analytics courses. Hopefully, we were able to provide you the insights you were looking for. Stay tuned for more exciting guides on data science.