Specialization Data Science

Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 26-lesson curriculum all about Machine Learning. In this curriculum, you will learn about what is sometimes called classic machine learning, using primarily Scikit-learn as a library and avoiding deep learning, which is covered in our forthcoming 'AI for Beginners' curriculum. Pair these lessons with our 'Data Science for Beginners' curriculum, as well! Travel with us around the world as we apply these classic techniques to data from many areas of the world. Each lesson includes pre- and post-lesson quizzes, written instructions to complete the lesson, a solution, an assignment, and more. Our project-based pedagogy allows you to learn while building, a proven way for new skills to 'stick'. ✍️ Hearty thanks to our authors Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu and Amy Boyd 🎨 Thanks as well to our illustrators Tomomi Imura, Dasani Madipalli, and Jen Looper 🙏 Special thanks 🙏 to our Microsoft Student Ambassador authors, reviewers, and content contributors, notably Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila, and Snigdha Agarwal 🤩 Extra gratitude to Microsoft Student Ambassadors Eric Wanjau, Jasleen Sondhi, and Vidushi Gupta for our R lessons!

There are 4 modules in this course AI isn't just for engineers. If you want your organization to become better at using AI, this is a course you should encourage everyone to take—especially your non-technical colleagues. In this course, you will learn: - The meaning of common AI terminology, including neural networks, machine learning, deep learning, and data science - What AI can—and cannot— actually do - How to find opportunities to apply AI to solve problems in your business organizations - What it's like to build machine learning and data science projects - How to work with an AI team and build an AI strategy in your company - How to navigate the ethical and public debate around AI Although this course is primarily non-technical, engineers can also take this course to learn about the business aspects of AI.

What you'll learn: ✔️Learn the skills needed to be successful in a machine learning engineering role ✔️Prepare for the Google Cloud Professional Machine Learning Engineer certification exam ✔️Understand how to design, build, productionalize ML models to solve business challenges using Google Cloud technologies ✔️Understand the purpose of the Professional Machine Learning Engineer certification and its relationship to other Google Cloud certifications Advance your career with in-demand skills: ✔️Receive professional-level training from Google Cloud ✔️Demonstrate your technical proficiency ✔️Earn an employer-recognized certificate from Google Cloud ✔️Prepare for an industry certification exam