The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field. This 3-course Specialization is an updated version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012.

The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.In this Specialization, you will build and train neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, Xavier/He initialization, and more. Get ready to master theoretical concepts and their industry applications using Python and TensorFlow and tackle real-world cases such as speech recognition, music synthesis, chatbots, machine translation, natural language processing, and more.

Covering descriptive and inferential statistics, as well as hypothesis testing techniques and exercises, statistics puts the “scientist” in data scientist. Statistics is the driving force in any quantitative career. It is the fundamental skill that a data scientist needs in order to understand and design statistical tests and analysis using modern software packages and programming languages. In this course, we start from the very basics and gradually build your statistical thinking. This, in turn, enables you to understand the more complex analyses carried out later in the program.

Learn how to master Power BI—one of the world’s most popular business intelligence tools—in this interactive learning path, co-created with Microsoft to pass the official PL-300 Data Analyst with Power BI exam. You’ll learn how to import, clean, manipulate, and visualize data in Power BI—all critical skills for any aspiring data professional. Through hands-on exercises, you'll learn data analysis best practices and discover a world of Power BI functionalities, including data modeling, DAX, Power Query, and many others.

The ability to build tools capable of retrieving and parsing information stored across the internet has been and continues to be valuable in many veins of data science.You will learn to navigate and parse html code, and build tools to crawl websites automatically. Although our scraping will be conducted using the versatile Python library scrapy, many of the techniques you learn in this course can be applied to other popular Python libraries as well, including BeautifulSoup and Selenium.

Gain the fundamental SQL skills you need to interact with and query your data. SQL is a powerful language used by data-driven businesses, large and small, to explore and manipulate their data to extract meaningful insights. In this track, you'll learn the SQL fundamentals you need to level up your data skills.

This course aims to teach everyone the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python. The course has no pre-requisites and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course. Once a student completes this course, they will be ready to take more advanced programming courses. This course covers Python 3.