Building computers and systems with the ability to think, learn, make decisions, and understand natural language is known as artificial intelligence (AI). AI is a branch of science and technology. AI is used in a wide range of fields, including healthcare, education, business, entertainment, and more. Microsoft has some useful free AI courses to improve your AI skills.
- A Machine Learning Overview
This introduction to machine learning for beginners concentrates on the main concepts. You will gain knowledge of the ML process, models, and data. Additionally, you will gain knowledge of several ML tasks, including classification, regression, clustering, and recommendation. - Overview of GitHub Copilot
The new AI-powered tool GitHub Copilot, which enables you to write code more effectively and quickly, is introduced in this session. OpenAI Codex, a sizable language model trained on trillions of lines of code, powers GitHub Copilot. It can also propose code snippets, functions, tests, comments, and other things. - Describe the Benefits of Using Cloud Services
Cloud computing, which provides computing services through the Internet, is covered in this course. You’ll discover why employing cloud services for your projects has advantages like scalability, dependability, security, cost-effectiveness, and innovation. Additionally, you will gain knowledge of several cloud service types, including serverless computing, infrastructure as a service, platform as a service, software as a service, and microservices. - Utilise Python to Analyse Data
Python is one of the most well-liked programming languages for data science, and this course serves as an introduction to data analysis using Python. You will learn how to manage, visualize, explore, and model data using Python libraries like pandas, numpy, matplotlib, seaborn, scikit-learn, etc. - Fundamentals of Generative AI
This course teaches generative AI, a subfield of artificial intelligence that focuses on producing original data or content, such as text, music, photos, etc. The concepts and uses of generative AI, including generative adversarial networks (GANs), variational autoencoders (VAEs), transformers, etc., will be covered.
