25 Experts have compiled this list of Best Free Data Science Online Course, Tutorial, Training, Class, and Certification available online for 2021. It includes both paid and free resources to help you learn about Free Data Science, and these courses are suitable for beginners, intermediate learners as well as experts.
8 Best Free Data Science Courses & Tutorials [2021 APRIL]
If you are looking for bestselling courses that allow you to build up the foundation of data science or take your existing skills a notch higher, then here you will find an array of suitable options. Analyze financial information, help innovate businesses, get an introduction to big data, ML, develop the ability of computational thinking, and much more. Upon the completion of the journey, you will be one step closer to your dream job.
– Mine, analyze, and visualize datasets and your findings.
– Choose from specialization tracks, individual courses, and certifications.
– Mini and capstone projects allow you to get hands-on.
– Learn from professors and university leaders.
– Lectures are accessible for free, and the verified certificate can be added at an additional price.
The massive amount of learning options available on the internet can make it confusing to find a curriculum that suits you. On this website, you will not only find top curated free and paid content but also a short quiz that will allow you to sort the best possible material to help you learn. Apart from this, there are bite-sized lessons that are handy for learning any particular topic quickly.
– Concise tutorials make it easy to study anytime.
– Free lessons available and the paid classes come with a 30-day money-back guarantee.
With being increasingly utilized in multiple industries, data science is rapidly becoming one of the fastest-growing fields. The learning platform edX has compiled a series of over 200 courses created by top academic and industrial institutions to aid your learning. Pick a programming language that you are comfortable with and get started with analyzing vast chunks of datasets.
Key USPs –
– The introductory programs do not need any prior experience in the field.
– Work with tools and languages like Excel, Python, R, and more.
– Choose among professional certifications, micromasters program, master’s degree.
– Some of the classes have a free trial period, whereas others let you self-learn for free.
This class offers an in-depth overview of this quickly evolving area and lets you learn by doing. Key topics discussed in the lessons include unsupervised and supervised learning, clustering, deep learning, and innovative solution. Lessons are accompanied by examples of how some of the top organizations are using these technologies to tackling real-world problems. With glowing ratings, this course is a crowd favorite.
– Use logistic and linear regression to classify data and predict accurate outcomes.
– Apply algorithms and draw insights from case studies.
– Explore the best practices followed by Silicon Valley.
– Introduction to neural networks and their uses.
– Use Octave or MATLAB to complete the assignments.
Primarily developed to assist students and professionals in gaining industry-ready skills, DataCamp leaves no stones unturned to provide you the best content available online. All relevant technologies and languages starting from Python, Shell, Git to SQL, and spreadsheets are covered. By completing the assignments and lectures, you will earn the certification of completion, which can be showcased in job applications.
– Various learning paths available based on your current expertise level.
– Apply your knowledge to solve real-life problems and develop your portfolio.
– Short and interactive challenges for practice.
– Continuous support is provided to make your journey smoother.
– The first few modules are available for a free trial.
This program is offered for individuals who are interested in taking up the role of data scientists but have no fundamental idea about the area. Instead of focusing entirely on a specific topic, the classes will stress on providing an overview of data science, the types of problems tackled under it, and some foundational techniques. By the ending, you will have a better sense of how to proceed with more advanced certification. Check out our compilation of Best Statistics Data Science Courses.
– No prior acquaintance with the covered concepts is mandatory.
– Manipulate datasets and analyze them using machine learning and statistics.
– Work with varying scales of information.
– Understand the importance of the visualization process.
– Interact with peers in the student community.
– Take the interactive quizzes and study at your own pace.
Get a chance to learn about machine learning from the experts of this technological powerhouse. Irrespective of whether you are a newbie or a seasoned individual, this website has something for you. The lectures comprise of a series of articles, videos, assignments. Begin by using the filter that asks you to select the type of your profession, the kind of content you are searching for, and the phase of ML you are interested in. Once you have answered these questions, you will get recommendations that suit your aspirations.
– Develop and debug your models and explore the latest algorithms.
– Mentors encourage you to learn by doing.
– Tools, best practices, and methods to develop and maintain AI products.
– Comics descriptions, demonstrations, and exercises make learning a fun experience.
– The study materials, lessons, and guides are accessible for free.
On edX, you will find real college curriculums on ML by the top institutions of the world as well as professional certifications from front running technological companies. These lectures not only help you to build a strong foundation but also introduce you to the latest trends in this field. If you want to work on a particular aspect of machine learning, then you can take the individual courses, or else you can go for the long series of training that comprises of multiple modules. Have a look at our take on Best Applied Data Science Courses.
– Draw conclusions from incomplete information, analyze and visualize them.
– Predict outcomes based on algorithms and hidden patterns.
– Use real-world examples to get a practical understanding.
– Get acquainted with tools and programming languages like GitHub, RStudio, Linux, Python.