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Our Courses
Try It: Intro to Spreadsheets
Excel skills are marketable in almost every industry. Whether you work in IT, healthcare, finance, or computer science, knowing how to operate spreadsheets can help you to organize data and gain valuable insights. This free, no-risk introductory course to spreadsheets aims to equip you with the beginner’s knowledge to navigate both Excel and Google Spreadsheets so you can bring greater solutions and organization to any project.
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Self Paced
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1
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English
Teaching Computational Thinking
This course is for educators who are passionate about the future of their 7-12+ year old students and want to learn more about teaching computer science in an engaging and meaningful way.
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Self Paced
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15
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English
An Introduction to Computer Networking for Teachers
Build your knowledge and understanding of computer networks as a computer science teacher.
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Self Paced
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12
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English
Impact of Technology: How To Lead Classroom Discussions
Learn how to keep 14-16 year-old students engaged in discussions while teaching computer science.
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Self Paced
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12
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English
Teaching Coding in Grades 5-8 with Scratch Encore
This course introduces teachers and other educators to the basics of teaching programming with Scratch to students in grades 5-8 using Scratch Encore, a culturally responsive, intermediate computer science curriculum. Each week, participants are introduced to key computer science concepts (e.g., loops, synchronization), and then apply those concepts as they complete programming assignments in Scratch. Helpful pedagogical practices and teaching strategies are introduced throughout the course.
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Self Paced
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English
Introduction to Computer Science and Programming
The term “Computation” refers to the action performed by a computer. A computation can be a basic operation and it can also be a sophisticated computer simulation requiring a large amount of data and substantial resources. This course aims at introducing learners with no prior knowledge to the basic key concepts of computer science. By following the lectures and exercises of this course, you will gain an understanding of algorithms by programming using the language Ruby.
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English
Introduction to Computer Science and Programming Using Python
An introduction to computer science as a tool to solve real-world analytical problems using Python 3.5.
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English
Computer Communications
This specialization is developed for seniors and fresh graduate students to understand fundamental network architecture concepts and their impacts on cyber security, to develop skills and techniques required for network protocol design, and prepare for a future of constant change through exposure to network design alternatives. Students will require a prior knowledge of C programming, an understanding of math probability and a computer science background is a plus.
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Self Paced
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English
Network Analysis for Marketing Analytics
Network analysis is a long-standing methodology used to understand the relationships between words and actors in the broader networks in which they exist. This course covers network analysis as it pertains to marketing data, specifically text datasets and social networks. Learners walk through a conceptual overview of network analysis and dive into real-world datasets through instructor-led tutorials in Python.
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Self Paced
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10 hours
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English
Mathematics for Machine Learning
For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in mathematics - stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to how it’s used in Computer Science.
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Self Paced
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English
Introduction to Data Science
Interested in learning more about data science, but don’t know where to start? This 4-course Specialization from IBM will provide you with the key foundational skills any data scientist needs to prepare you for a career in data science or further advanced learning in the field. This Specialization will introduce you to what data science is and what data scientists do. You’ll discover the applicability of data science across fields, and learn how data analysis can help you make data driven decisions.
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English
C++ Basic Structures: Vectors, Pointers, Strings, and Files
Code and run your first C++ program in minutes without installing anything! This course is designed for learners with limited coding experience, providing a solid foundation of not just C++, but core Computer Science topics that can be transferred to other languages. The modules in this course cover vectors, pointers, strings, and files. Completion of C++ Basics: Selection and Iteration before taking this course is recommended. To allow for a truly hands-on, self-paced learning experience, this course is video-free.
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Self Paced
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9 hours
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English
Teaching Impacts of Technology: Workplace of the Future
In this course you’ll focus on how the Internet has enabled new careers and changed expectations in traditional work settings, creating a new vision for the workplace of the future. This will be done through a series of paired teaching sections, exploring a specific “Impact of Computing” in your typical day and the “Technologies and Computing Concepts” that enable that impact, all at a K12-appropriate level.
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Self Paced
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13 hours
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English
Data Mining
The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp. Courses 2 - 5 of this Specialization form the lecture component of courses in the online Master of Computer Science Degree in Data Science.
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Self Paced
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English
Introduction to Machine Learning: Supervised Learning
In this course, you’ll be learning various supervised ML algorithms and prediction tasks applied to different data. You’ll learn when to use which model and why, and how to improve the model performances. We will cover models such as linear and logistic regression, KNN, Decision trees and ensembling methods such as Random Forest and Boosting, kernel methods such as SVM. Prior coding or scripting knowledge is required. We will be utilizing Python extensively throughout the course.
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Self Paced
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40 hours
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English
Statistics for Data Science with Python
This Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and procedures used for data analysis. After completing this course you will have practical knowledge of crucial topics in statistics including - data gathering, summarizing data using descriptive statistics, displaying and visualizing data, examining relationships between variables, probability distributions, expected values, hypothesis testing, introduction to ANOVA (analysis of variance), regression and correlation analysis.
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Self Paced
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14 hours
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English
Teaching Impacts of Technology in K-12 Education
2% That’s the estimate of how many high school students in all of California took a Computer Science class in 2015. And yet, computers and data are everywhere. Just consider a typical 24 hours in your life … how many different computer devices do you use?
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Self Paced
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English
CS50's Computer Science for Business Professionals
This is CS50’s introduction to computer science for business professionals.
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Self Paced
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32
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English
Basic Modeling for Discrete Optimization
Optimization is a common form of decision making, and is ubiquitous in our society. Its applications range from solving Sudoku puzzles to arranging seating in a wedding banquet. The same technology can schedule planes and their crews, coordinate the production of steel, and organize the transportation of iron ore from the mines to the ports. Good decisions in manpower and material resources management also allow corporations to improve profit by millions of dollars.
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Self Paced
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28 hours
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English
Object-Oriented Python: Inheritance and Encapsulation
Code and run your first python program in minutes without installing anything! This course is designed for learners with limited coding experience, providing a solid foundation of not just python, but core Computer Science topics that can be transferred to other languages. The modules in this course cover inheritance, encapsulation, polymorphism, and other object-related topics. Completion of the prior 3 courses in this specialization is recommended. To allow for a truly hands-on, self-paced learning experience, this course is video-free.
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Self Paced
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10 hours
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English
Health Data Science Foundation
This course is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios. We cover deep learning (DL) methods, healthcare data and applications using DL methods.
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Self Paced
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24 hours
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English
Generalized Linear Models and Nonparametric Regression
In the final course of the statistical modeling for data science program, learners will study a broad set of more advanced statistical modeling tools. Such tools will include generalized linear models (GLMs), which will provide an introduction to classification (through logistic regression); nonparametric modeling, including kernel estimators, smoothing splines; and semi-parametric generalized additive models (GAMs). Emphasis will be placed on a firm conceptual understanding of these tools.
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Self Paced
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42 hours
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English
Applied Data Science
This action-packed Specialization is for data science enthusiasts who want to acquire practical skills for real world data problems. If you’re interested in pursuing a career in data science, and already have foundational skills or have completed the Introduction to Data Science Specialization, this program is for you! This 4-course Specialization will give you the tools you need to analyze data and make data driven business decisions leveraging computer science and statistical analysis.
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Self Paced
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English
Digital Signal Processing 1: Basic Concepts and Algorithms
Digital Signal Processing is the branch of engineering that, in the space of just a few decades, has enabled unprecedented levels of interpersonal communication and of on-demand entertainment. By reworking the principles of electronics, telecommunication and computer science into a unifying paradigm, DSP is a the heart of the digital revolution that brought us CDs, DVDs, MP3 players, mobile phones and countless other devices. In this series of four courses, you will learn the fundamentals of Digital Signal Processing from the ground up.
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Self Paced
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29 hours
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English
Effective Communication Capstone Project
In the Effective Communication Capstone learners apply the lessons of Business Writing, Graphic Design, and Successful Presentation to create a portfolio of work that represents their mastery of writing, design, and speaking and that expresses their personal brand. The portfolio includes three individual elements—a written memo, a slide deck, and a presentation—integrated around a single topic. We provide the elements for a basic capstone, but we also invite our learners to create their own project if they so choose.
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Course by
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Self Paced
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14 hours
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English