Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
Our Courses
Computational Thinking for K-12 Educators Capstone
In this capstone project course, you will learn to support your students in successfully completing the Advanced Placement Principles Create Task -- however this task can be useful for any course as a culminating, student-designed final programming project. You will learn to interpret and practice applying to real sample student work the Create Task rubric and have the option to modify it for your own setting.
-
Course by
-
Self Paced
-
11 hours
-
English
Linux: I/O Redirection for DevOps
In this 1-hour long project-based course on Linux i/o redirection for DevOps you will be working entirely on the command line and using powerful Linux commands and redirection operators to learn how input and output redirection works in Linux. You will get experience of taking control of what happens to the stdin and stdout of all your commands and no longer be confused about the details on how piping and redirection works in Linux. This course is designed for any person working or who intends to work with Linux, from Linux system administrators to developers and DevOps practitioners.
-
Course by
-
Self Paced
-
3 hours
-
English
Introduction to Deep Learning
Deep Learning is the go-to technique for many applications, from natural language processing to biomedical. Deep learning can handle many different types of data such as images, texts, voice/sound, graphs and so on. This course will cover the basics of DL including how to build and train multilayer perceptron, convolutional neural networks (CNNs), recurrent neural networks (RNNs), autoencoders (AE) and generative adversarial networks (GANs).
-
Course by
-
Self Paced
-
60 hours
-
English
ANOVA and Experimental Design
This second course in statistical modeling will introduce students to the study of the analysis of variance (ANOVA), analysis of covariance (ANCOVA), and experimental design. ANOVA and ANCOVA, presented as a type of linear regression model, will provide the mathematical basis for designing experiments for data science applications. Emphasis will be placed on important design-related concepts, such as randomization, blocking, factorial design, and causality.
-
Course by
-
Self Paced
-
40 hours
-
English
Problem Solving, Python Programming, and Video Games
This course is an introduction to computer science and programming in Python. Upon successful completion of this course, you will be able to: 1. Take a new computational problem and solve it, using several problem solving techniques including abstraction and problem decomposition. 2. Follow a design creation process that includes: descriptions, test plans, and algorithms. 3.
-
Course by
-
Self Paced
-
80 hours
-
English
Introduction to Machine Learning with Python
This course will give you an introduction to machine learning with the Python programming language. You will learn about supervised learning, unsupervised learning, deep learning, image processing, and generative adversarial networks. You will implement machine learning models using Python and will learn about the many applications of machine learning used in industry today. You will also learn about and use different machine learning algorithms to create your models. You do not need a programming or computer science background to learn the material in this course.
-
Course by
-
Self Paced
-
13 hours
-
English
Successful Presentation
Few kinds of communication can have the effect of a powerful presentation. Even a short speech can motivate people to change long-held beliefs or to take action, and a wonderfully delivered speech can transform a normal person into a leader. In this course, Prof. William Kuskin provides a series of pragmatic videos and exercises for successful public speaking and presentations.
-
Course by
-
Self Paced
-
21 hours
-
English
Basic Game Development with Levels using Scratch
By the end of this project, you will create a basic game using additional features with an introductory, web-based coding program called Scratch. Learning to code will allow you to build basic coding or computer science skills and a fundamental understanding in order to grow your programming abilities. Learners will engage in the design process in order to develop an understanding of how to develop algorithms that control programs, use event-driven programming, and debug a program.
-
Course by
-
Self Paced
-
2 hours
-
English
Delivery Problem
In this online course we’ll implement (in Python) together efficient programs for a problem needed by delivery companies all over the world millions times per day — the travelling salesman problem. The goal in this problem is to visit all the given places as quickly as possible. How to find an optimal solution to this problem quickly? We still don’t have provably efficient algorithms for this difficult computational problem and this is the essence of the P versus NP problem, the most important open question in Computer Science.
-
Course by
-
Self Paced
-
13 hours
-
English
Classical Cryptosystems and Core Concepts
Welcome to Introduction to Applied Cryptography. Cryptography is an essential component of cybersecurity. The need to protect sensitive information and ensure the integrity of industrial control processes has placed a premium on cybersecurity skills in today’s information technology market. Demand for cybersecurity jobs is expected to rise 6 million globally by 2019, with a projected shortfall of 1.5 million, according to Symantec, the world’s largest security software vendor. According to Forbes, the cybersecurity market is expected to grow from $75 billion in 2015 to $170 billion by 2020.
-
Course by
-
Self Paced
-
12 hours
-
English
Communicating Data Science Results
Important note: The second assignment in this course covers the topic of Graph Analysis in the Cloud, in which you will use Elastic MapReduce and the Pig language to perform graph analysis over a moderately large dataset, about 600GB. In order to complete this assignment, you will need to make use of Amazon Web Services (AWS). Amazon has generously offered to provide up to $50 in free AWS credit to each learner in this course to allow you to complete the assignment.
-
Course by
-
Self Paced
-
8 hours
-
English
Data Science with NumPy, Sets, and Dictionaries
Become proficient in NumPy, a fundamental Python package crucial for careers in data science. This comprehensive course is tailored to novice programmers aspiring to become data scientists, software developers, data analysts, machine learning engineers, data engineers, or database administrators. Starting with foundational computer science concepts, such as object-oriented programming and data organization using sets and dictionaries, you'll progress to more intricate data structures like arrays, vectors, and matrices.
-
Course by
-
Self Paced
-
31 hours
-
English
AI, Business & the Future of Work
This course from Lunds university will help you understand and use AI so that you can transform your organisation to be more efficient, more sustainable and thus innovative. The lives of people all over the world are increasingly enhanced and shaped by artificial intelligence. To organisations there are tremendous opportunities, but also risks, so where do you start to plan for AI, business and the future of work? Whether you are in the public or private sector, in a large organisation or a small shop, AI has a growing impact on your business.
-
Course by
-
Self Paced
-
12 hours
-
English
Resampling, Selection and Splines
"Statistical Learning for Data Science" is an advanced course designed to equip working professionals with the knowledge and skills necessary to excel in the field of data science. Through comprehensive instruction on key topics such as shrink methods, parametric regression analysis, generalized linear models, and general additive models, students will learn how to apply resampling methods to gain additional information about fitted models, optimize fitting procedures to improve prediction accuracy and interpretability, and identify the benefits and approach of non-linear models.
-
Course by
-
Self Paced
-
16 hours
-
English
Java Basic Structures: Arrays, Strings, and Files
Code and run your first Java program in minutes without installing anything! This course is designed for learners with limited coding experience, providing a solid foundation of not just Java, but core Computer Science topics that can be transferred to other languages. The modules in this course cover arrays, strings, and files. Completion of Java 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.
-
Course by
-
Self Paced
-
7 hours
-
English
An Introduction to Logic for Computer Science
Logic plays a fundamental role in computer science. This course is designed to equip you with a solid understanding of the fundamental principles of logic and their relevance in the field of computer science. In this course, you'll explore proposition logic and discover its practical applications in problem-solving, algorithm design, and the development of intelligent systems. By engaging in hands-on exercises, exploring real-world examples, and participating in discussions, you'll develop strong logical reasoning and critical thinking skills.
-
Course by
-
Self Paced
-
7 hours
-
English
Introduction to Computer Vision
Introduction to Computer Vision guides learners through the essential algorithms and methods to help computers 'see' and interpret visual data. You will first learn the core concepts and techniques that have been traditionally used to analyze images. Then, you will learn modern deep learning methods, such as neural networks and specific models designed for image recognition, and how it can be used to perform more complex tasks like object detection and image segmentation.
-
Course by
-
Self Paced
-
8 hours
-
English
Foundations of Computer Science
Welcome to Introduction to Programming: Visual Basic. In the course sequence you will learn to write programs that utilize both procedural and object oriented techniques to solve business problems. In the first course in the sequence we will provide you with a solid foundation in the computer science topics that are important to understand when programming Visual Basic. In courses two through four, we will role up our sleeves and start coding in Visual Basic. In these courses you need to have access to a computer that is running Windows, macOS or Linux with the .NET 5 installed.
-
Course by
-
Self Paced
-
16 hours
-
English
Process Map Data using C++ Adjacency List Shortest Path
In this project you will use the adjacency list data structure and other data structures to find the shortest distance between a set of towns loaded from a file. The shortest path problem is well known in the field of computer science. An adjacency list is probably the best data structure to represent a set of connected vertices to find the shortest path from one vertex to another. One application for shortest paths is in computer networking routing.
-
Course by
-
Self Paced
-
2 hours
-
English
Teaching Impacts of Technology: Data Collection, Use, and Privacy
In this course you’ll focus on how constant data collection and big data analysis have impacted us, exploring the interplay between using your data and protecting it, as well as thinking about what it could do for you in 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.
-
Course by
-
Self Paced
-
13 hours
-
English
System Validation (2): Model process behaviour
System Validation is the field that studies the fundamentals of system communication and information processing. It is the next logical step in computer science and improving software development in general. It allows automated analysis based on behavioural models of a system to see if a system works correctly. We want to guarantee that the systems does exactly what it is supposed to do. The techniques put forward in system validation allow to prove the absence of errors.
-
Course by
-
Self Paced
-
5 hours
-
English
Data Mining Pipeline
This course introduces the key steps involved in the data mining pipeline, including data understanding, data preprocessing, data warehousing, data modeling, interpretation and evaluation, and real-world applications. This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history.
-
Course by
-
Self Paced
-
22 hours
-
English
Teaching Impacts of Technology: Relationships
In this course you’ll focus on how “smart” devices have changed how we interact with others in personal ways, impacting how we stay connected in our increasingly mobile society. 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.
-
Course by
-
Self Paced
-
11 hours
-
English
Cybersecurity for Data Science
This course aims to help anyone interested in data science understand the cybersecurity risks and the tools/techniques that can be used to mitigate those risks. We will cover the distinctions between confidentiality, integrity, and availability, introduce learners to relevant cybersecurity tools and techniques including cryptographic tools, software resources, and policies that will be essential to data science.
-
Course by
-
Self Paced
-
19 hours
-
English
Python Basics: Selection and Iteration
Code and run your first python program in minutes without installing anything! This course is designed for learners with no 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 printing, operators, iteration (i.e., loops), and selection (i.e., conditionals). To allow for a truly hands-on, self-paced learning experience, this course is video-free.
-
Course by
-
Self Paced
-
9 hours
-
English