Top 11 Free and Best AI/Data Science Courses
Universities and educational institutions around the world are investing heavily in making learning AI accessible to everyone. Universities in India are also introducing new courses to meet the growing demand for AI and data experts.
Over the past few years, artificial intelligence (AI) has developed into an ever-evolving and fast-growing field. It is widely used in many fields and fields to study and analyze data, find hidden patterns, as well as make meaningful decisions in real life.
The global artificial intelligence market is estimated at $35.92 billion in 2020. According to Fortune Business Insights, the market is projected to reach $360.36 billion by 2028, growing at a CAGR of 33.6% between 2020 and 2028. Investments in artificial intelligence are projected to reach $1 billion by 2023. In fact, the Indian government allocated $477 million to the artificial intelligence ecosystem in India last year.
To take full advantage of this opportunity, universities and educational institutions around the world are investing heavily in making learning AI accessible to everyone. Universities in India are also introducing new courses to meet the growing demand for AI and data experts.
Unnati Program | Intel
Semiconductor company Intel launched the Intel Unnati program to provide Indian engineering students with the data center skills they need. Intel also plans to set up 100 Intel Unnati DataCentric Labs next year in engineering and universities with a focus on research and innovation. The program allows students to effectively combine Intel FPGA hardware and software to accelerate workloads for CPU-intensive tasks. A joint Intel certification is awarded upon completion of the program.
Machine Learning for Beginners | Microsoft x MIT
Microsoft has launched a 12-week MIT-approved machine learning course for beginners. The 26-class curriculum teaches students classic machine learning using Scikitlearn. Topics include: Introduction to Machine Learning, its History, Fairness in Machine Learning, Machine Learning Methods, Introduction to Regression, Classification, Clustering, NLP Tasks, Translation and Sentiment Analysis, Time Series Prediction, Reinforcement Learning, and more.
re/Start | AWS
Amazon Web Service (AWS) re/Start is a face-to-face skills development and training program designed to help beginners connect and collaborate with potential employers in the cloud. In this course, students will learn the basics of the AWS Cloud and will be able to create using Linux, Python, networking, security, and relational databases. The program is currently being implemented in Bangalore, Kolkata, Chennai, Pune and Thiruvananthapuram.
AI Search Methods for Problem Solving | IIT Madras
Indian Institute of Technology, Madras 12-week AI course is offered on the National Program for Advanced Learning (NPTEL) platform and is delivered by Professor Deepak Kehmanu in the Department of Computer Science and Engineering. The course is free, but you have to pay 1000 rupees to take the exam.
AI and Data Science Upscaling for Youth of Punjab
Indian Institute of Technology, Ropar and Punjab Skills Development Mission have teamed up to provide free AI and data science courses for youth in Punjab. It is open to 12th grade students with mathematical backgrounds. This program includes two modular programs. L2 program for 4 weeks; and an L3 program for 12 weeks. Upon completion of the course, students will receive a Certificate of Completion from IIT Ropar.
Building trusted AI products | Google
Upon completion of this coding program, students will be able to create powerful and user-centric AI products with the People + AI Research (PAIR) guide. Students will also learn about the latest additions to the second edition of the PAIR Guidebook and complete a series of exercises highlighting the capabilities of the AI development process to calibrate user trust with a focus on data and user explainability. You will also be introduced to the wider range of materials and resources available.
Data Science: Machine Learning | Harvard x EdX
This machine learning course is offered by Harvard University as part of a large professional certification program in data science. This course focuses on data analysis and statistics and aims to help students create a recommendation system for movies and explore the scientific underpinnings of popular data processing techniques. Please post the completion of this course. Students learn the basics of machine learning, how to cross-validate to avoid overtraining, popular machine learning algorithms, regularization, and their usefulness. Assuming students spend 2-4 hours per week, the estimated time required to complete the course is 8 weeks.
Data Science Specialisation | Coursera
This data science specialization is offered by Johns Hopkins University and helps students start their data science careers. Students learn how to use R to organize, analyze, and visualize data. Perform regression analysis and inference using regression models to explore data processing pipelines from data collection to publication. I use GitHub to manage my data science projects.
This beginner course lasts approximately 11 months and includes 10 specialization modules. Course instructors are Jeff Leek, Associate Professor of Biostatistics, Roger D. Peng, Associate Professor of Biostatistics, and Brian Kaffo, Associate Professor of Biostatistics.
Data Science Foundations | CognitiveClass.ai
The CognitiveClass.ai Data Science Foundation for Beginners consists of three courses.
Introduction to Data Science: Learn about data science practices and gain a general understanding of the field.
Data Analysis Methodology: Learn to solve data science problems, collect and analyze data, create models, and understand feedback after model deployment.
Data Science Tools: Learn about popular data processing and visualization tools such as Jupyter Notebooks, RStudio IDE, IBM Watson Studio, and more.
Introduction to Computational Thinking and Data Science | MIT x EdX
MIT's introductory courses in computational thinking and data science include advanced Python 3 programming, backpack problems, graphs and graph optimization, dynamic programming, Pylab graphs, probability, distribution, and statistical errors. This is a course mentioned by John Guttag, Eric Grimson, and Ana Bell of MIT. The estimated time for this course is 9 weeks, assuming students spend 14-16 hours per week.
Data Mining course | KDNuggets
KDNuggets' Introductory Data Mining course is a first-semester introductory data mining course for first-year undergraduate and graduate students. This course was created by Dr. Gregory Pyatetsky Shapiro and Professor Gary Parker. Topics such as machine learning and data mining, machine learning and classification, regression, visualization, generalization, and targeted marketing are covered.