Top 7 Free Data Science Online Courses [For Freshers & Experienced]

Demand for data science experts has been on the rise. IBM recently predicted a 28% increase in the number of employed data scientists in the upcoming years. In today’s data-driven world, every organisation has joined the data collection race to extract valuable insights.

The organisations are expanding and rapidly turning data-driven. The data allows the organisations to be accurate with the findings that help them in effective decision making, as well as it helps the organisations to respond to the market trends rapidly. With the increase in the options available, the companies want to cater to their customer’s demands and provide customer-centric products, so to understand what the customer wants, data helps. Along with that, data allows the companies to acquire more customers and retain the existing customers, eventually contributing to the revenue and growth of the company. 

Data Science’s application is not limited to the revenue enhancement of the company; it has a much wider application. It is helpful in the healthcare sector, banking, manufacturing, transport, etc. The data brings accuracy in the judgment, which comes through various algorithms that run behind.

The varied application of data science leads to the significant demand for data science professionals in today’s age, and that is reflected in the salary the data science professionals procure. Data science jobs are among the top-paying jobs in the market right now. The average salary of a data scientist is 10.5 LPA. 

annual data science salary


Data science has many job roles to choose from, and it is not restricted to being a data scientist only. The various job roles that are available in the data science industry are-

  1. Data Scientist
  2. Data Analyst
  3. Data Administrator
  4. Data Engineer
  5. Statistician
  6. Data Science Manager
  7. Business Analyst
  8. Data Journalist
  9. Decision Scientist
  10. Big Data Analyst
  11. Data Architect
  12. MIS Consultant
  13.  Data Visualisation Consultant

These insights are fundamental for companies since it helps them to build relevant solutions, design targeted marketing strategies, and make data-oriented business decisions – no wonder why organisations across all industries are increasingly investing in data science technologies. 

Apart from being a flourishing field, data science also welcomes students from different backgrounds – from computer science to economics and statistics to cognitive science. So, even if you’re not from a data science background, you don’t need to feel left out. With a few courses, certifications, and data science projects, you’ll be up to speed with all that’s needed for building a successful career in data science. Aspiring to enter data science is a realistic dream today with a multitude of opportunities to learn data science for free with certificate. The opportunity to study free gives the advantage to study and get through with the basics and the certificates are an added advantage providing a testimonial to your skillset while approaching a potential employer.

Lucky for you, there are various free online data science courses and tutorial that can help you not only set your foundations right but also get hands-on experience of working with new technologies. 

Why Pursue a Free Data Science Course?

As we mentioned earlier, employers worldwide now recognise the importance of hiring candidates skilled in dealing with large chunks of data for information extraction. Modern challenges require innovative solutions, and hence, it is crucial for professionals to acquire trending industry skills like data science and data analytics

Today, with various automated tools and technologies to handle mundane and repetitive tasks like data cleaning, preparing, analysing, many elements of data science have become much more accessible. So, people can carry out data-driven operations (like predictive modelling) without needing to get their hands dirty with any coding or algorithms. However, this is a very mechanical approach to things. 

If you have a clear understanding of the fundamentals behind these automated tools, you’ll be in a much better position to use these tools more productively. You’ll develop a different perspective towards these tools once you get a grasp of their inner workings. Also, you might be able to create more optimised techniques to solve complex business problems.

Data Science allows companies to work with huge data and draw valuable and actionable insights from them. The companies can track the progress, metrics, customer satisfaction, and important metrics with the help of data science. With the help of algorithms, languages, and tools a task that would normally take days to accomplish gets finished in a shorter span of time. This is another reason why free data science & big data courses have become necessary for professionals aiming to get into the industry. Also, professionals who are already in the industry get an added advantage of revisiting the concepts and getting their basics clear before upskilling to a higher rigor course.

Because of this reason, we recommend you enrol in a data science free online course. By taking up an online course, you can learn from the safety and comfort of your home. While some online data science courses offer certificates of completion, some don’t. So, make sure to check the course webpage for the course details.  

Top Data Science Free Online Courses

upGrad – Free Data Science Certification Courses

upStart – an upGrad initiative – is aimed at helping students and professionals learn about the latest technologies and advancements free of cost. These courses are designed to introduce beginners to practical, real-world problems. 

1. Programming with Python – Introduction for Beginners

If you want to learn about the nuances of programming using Python, and how that helps you in your Data Science career – this course is precisely for you. Everything from data structures, programming paradigms, control structures, Object-Oriented Programming to building real-world solutions using Python is covered in this comprehensive course for beginners. It spans 17 hours and gives you a complete walkthrough of Python programming. 

Python is a highly purposeful programming language. It is widely used in the industry and is one of the demanded languages. Python is majorly used to build websites, software, data visualisations, etc. Along with that it has its own sets of advantages such as it is easily readable, simple to use, object-oriented, extensive libraries, portable, etc. Because python is vastly used and accepted, this course becomes one of the best data science courses online free, this is an opportunity to upskill toward better career advancement.

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2. Learn Basic Python Programming

Learn about lists, tuples, strings, and other important programming constructs from the lens of Python programming language in this 15-hour long course aimed at beginners. Set yourself up for learning advanced programming concepts, techniques, and diving deeper into the world of Data Science by completing this course.

There are various contributing factors to learning basic python programming such as, it improves productivity, helps in the finance sector and trading industry, facilitates testing, dynamically typed, free and open source, etc. The benefits make python programming one of the top data science courses online.

3. Learn Python Libraries: NumPy, Matplotlib, and Pandas

Beginner-friendly yet comprehensive – this course on Python libraries familiarises you with the different libraries you’ll need throughout your Data Science career. Numpy, Matplotlib, and Pandas are some of the most useful Python libraries for working with large chunks of data and deriving insights from it. This introductory course will help you take on fundamental data science challenges using Python libraries. 

take on fundamental data science challenges using Python libraries. 

Numpy provides multidimensional arrays as it takes less memory space and runs fast. Numpy supports bitwise operators, arithmetic operations, linear algebra, matrix operations, stacking, searching, sorting, counting, etc. 

Matplotlib supports graphical representation as the name suggests. The graphical representation could be anything based on preference, such as bar graphs,  line graphs, histograms, scatter graphs, etc. Matplotlib facilitates the visual representation of the data which are static, animative, and interactive.

Pandas is another python library used for data analysis. It works with data representation seamlessly, is known for handling large sets of data, and provides an opportunity to customise the data by proving certain features. It is commonly used for data science and machine learning, where it facilitates data cleansing and analysing. These libraries and usages make for another reason why data scientist online course free is an opportunity to get an advantage in the workforce.

4. Introduction to Natural Language Processing

Natural Language Processing is all about understanding human linguistics and modelling it for computing machines to understand. It has implications all across different industries – from entertainment to healthcare to customer service. Go through this 11-hour course to understand the basics of Natural Language Processing and use regex to build spell correction, phonetic hashing, and spam detection tools.

Natural Language is a branch of computer science and mainly artificial intelligence which gives the computer capability to understand textual and spoken language in a similar way a human being does. The NLP market is projected to reach  $341,530.29 million by 2030, growing at a CAGR of 40.9% from 2020 to 2030. The applications of NLP are all around us such as Siri, Alexa, Google Assistant, etc. Because of its projected growth and highly acceptable demand for NLP professionals, it is considered one of the top data science courses online.

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5. Fundamentals of Deep Learning of Neural Networks

If you’re fascinated by deep learning and want to understand how the neuronal structure of our brain is replicated to make machines smarter – this course is for you. Go through this course to learn about neural networks, learning in neural networks, recurrent networks, feedback and feed-forward learning mechanisms, and some concepts of deep learning that involve higher applications of neural networks. Running for 28 hours, this course is your perfect entry point to the world of Neural Networks and Deep Learning.

Deep Learning is a type of ML and AI where it allows the machine to learn new knowledge the way human beings do use neural networks. The Deep Learning market is expected to reach USD 18.16 Billion by 2023, at a CAGR of 41.7% from 2018 to 2023. There are various examples of deep learning such as virtual assistants, driverless transportation, facial recognition, etc. Its popularity contributes to deep learning being one of the best data science courses online free.

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6. Basics of Inferential Statistics

Statistics is an important component of the entire Data Science spectrum – and inferential statistics more so. After all, Data Science is more about understanding and making sense of data than just data collection. In this course, you will learn how to use the right tools and techniques for carrying out inferential statistics on datasets. Learn about probability and statistics, continuous-discrete probability distributions, sampling methods and their error quantification, and central limit theorem in this 15-hour course!

Inferential statistics is a field of statistics that uses relevant tools in order to analyse and draw inferential conclusions from the research. 

upGrad’s Exclusive Data Science Webinar for you –

How upGrad helps for your Data Science Career?


7. Data Science in E-commerce

E-commerce is a growing industry. This course will introduce you to all the data science and analytics that goes on in the back-end of any e-commerce business. Take this 13-hour course to get a deeper understanding of how data-driven decisions are made in the e-commerce business and get introduced to the important tools and techniques.

Data science has become a major reason behind the boom in the e-commerce industry. There is huge competition in the market and the various options available to choose from have made the industry competitive. The trends are constantly changing so is consumer behavior. If there is any delay in reacting to these trends, the company stands a chance to lose its customers. 

Data science has given an opportunity for companies to track the metrics and react appropriately. The data has brought accuracy to the company’s operations. E-commerce utilises the data from identifying their consumers, placing and marketing their products to receiving the feedback and actioning upon it. The company always aims to increase revenue by providing consumer-centric products, acquiring new consumers to retaining the existing consumers.

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Data Science is no longer a buzzword – it’s the need of the hour for every organisation looking to improve their services by gathering valuable business insights. As a result, companies reward data science professionals with hefty annual packages. 

So, if you’re fascinated by the world of data and want to add value by solving real-world data science problems, the courses mentioned above are great for breaking the ice. You can either pick one or multiple courses, depending on your bandwidth and capacity. The idea is to complete whatever course(s) you opt for while working on real-world projects. It enables you to gain a deeper understanding of the theoretical knowledge you’ve acquired. 

If you are curious to learn more about data science, check out IIIT-B & upGrad’s Executive PG Program in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms.

Freshers, mid-level managers, and senior executives can also opt for upGrad’s Advanced Certificate Programme in Machine Learning which is a 7 months course designed to teach aspirants to be industry leaders. The ML course is offered in collaboration with IIT Delhi and requires students to take a 40-minute entrance test on programming and mathematics, on the basis of which their applications are shortlisted. Being a reputed educational institute in India, IITD aims at accelerating your career growth by providing access to world-class faculty and mentors who help students build ML capabilities and lead functional teams. There are 20 live sessions included in this advanced certificate program that cover 14 data science subjects. 

Here’s an opportunity you don’t want to miss. 

We hope this article introduced you to one, if not many, useful courses that you can take!

Can I learn Data Science from home?

Yes, you can definitely learn data science on your own. The best way to start learning about data science is to take up an online course. Online courses and classes are the perfect way to learn everything from beginner to advanced level. Whether it is theoretical knowledge or practical application of the technology, you can get the right training with the help of an online course in the comfort of your home.
You just need to make sure that you are taking up the right course so that you get to learn all the necessary concepts for data science. With dedication and consistent application of the gained knowledge, you can definitely learn data science on your own.

How do I start Data Science from scratch?

Data Science has become a dream field for several people out there. People often find it confusing because they don't know where to begin their learning journey. If you also find it challenging to start with this learning journey, then let's make it easy for you.
By following the below step-by-step procedure, you will find it pretty easy to start your data science learning journey.
1. Get familiar with the basics of Python programming
2. Understand the fundamentals of Mathematics and Statistics.
3. Get clear with the concepts of Python with Data Analysis
4. Start learning Machine Learning
5. Practice different projects to apply the gained knowledge

Is Data Science a stressful job?

Every job has its ups and downs. There is a learning curve in every job, and it will take some time to get familiar with all the tools being used for that particular job in the company. It will sound a bit stressful when you are beginning with the learning phase, but you will be able to figure it out down the line. If you find the data science job really interesting, then you will never get stressed, even if you have a lot to learn and a lot to work upon.

How do I become a data scientist?

In order to become a data scientist one need to begging by acquiring the basic education relevant to the field such as graduation, science, computer science, mathematics, statistics, B.Tech, or other science-related fields. Then procurement of gaining basic data science understanding through good and relevant certifications or diploma courses should be done. Gain work experience, get more skills, network, and keep upskilling to advance the career.

How much money can you make as a data scientist?

Data science is considered as one of the high-paying careers. The average salary for a data scientist is ₹ 10.5 LPA

Can a beginner learn data science?

Yes, a beginner can learn data science. They should have completed their basic education in the field of science, computer science, mathematics, statistics, or other science-related fields. Then they should invest the time in getting certification or diplomas. Once the foundation has been laid, get an internship or land a job to kickstart a career in data science.

Is data science in demand?

Data science is a very demanded field in today’s time. The market for data science is continuously growing as data is becoming the center for organisations. The market for data science is expected to grow by USD 25.94 billion by 2027.

Can I become a data scientist with no experience?

Yes, it is possible to become a data scientist with no experience. But there are certain conditions such as the aspirant should be having a relevant understanding of the programming language and tools. They should be aware of the data cleaning methods and techniques. If someone has relevant knowledge and understanding of the domain, they can definitely land a job and begging their career in data science.

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