Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
Our Courses
Business Statistics and Analysis Capstone
The Business Statistics and Analysis Capstone is an opportunity to apply various skills developed across the four courses in the specialization to a real life data. The Capstone, in collaboration with an industry partner uses publicly available ‘Housing Data’ to pose various questions typically a client would pose to a data analyst. Your job is to do the relevant statistical analysis and report your findings in response to the questions in a way that anyone can understand. Please remember that this is a Capstone, and has a degree of difficulty/ambiguity higher than the previous four courses.
-
Course by
-
7 hours
-
English
The Structured Query Language (SQL)
In this course you will learn all about the Structured Query Language ("SQL".) We will review the origins of the language and its conceptual foundations. But primarily, we will focus on learning all the standard SQL commands, their syntax, and how to use these commands to conduct analysis of the data within a relational database.
-
Course by
-
Self Paced
-
55 hours
-
English
Introduction to Self-Driving Cars
Welcome to Introduction to Self-Driving Cars, the first course in University of Toronto’s Self-Driving Cars Specialization. This course will introduce you to the terminology, design considerations and safety assessment of self-driving cars.
-
Course by
-
Self Paced
-
35 hours
-
English
Algorithms for Searching, Sorting, and Indexing
This course covers basics of algorithm design and analysis, as well as algorithms for sorting arrays, data structures such as priority queues, hash functions, and applications such as Bloom filters. Algorithms for Searching, Sorting, and Indexing can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others.
-
Course by
-
Self Paced
-
35 hours
-
English
Predictive Modeling and Analytics
Welcome to the second course in the Data Analytics for Business specialization! This course will introduce you to some of the most widely used predictive modeling techniques and their core principles. By taking this course, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data. You will learn how to carry out exploratory data analysis to gain insights and prepare data for predictive modeling, an essential skill valued in the business.
-
Course by
-
11 hours
-
English
Semiconductor Physics
This course can also be taken for academic credit as ECEA 5630, part of CU Boulder’s Master of Science in Electrical Engineering degree. This course introduces basic concepts of quantum theory of solids and presents the theory describing the carrier behaviors in semiconductors. The course balances fundamental physics with application to semiconductors and other electronic devices. At the end of this course learners will be able to: 1. Understand the energy band structures and their significance in electric properties of solids 2. Analyze the carrier statistics in semiconductors 3.
-
Course by
-
Self Paced
-
15 hours
-
English