Our Courses

Architecture, Algorithms, and Protocols of a Quantum Computer and Quantum Internet

Learn how a quantum computer can be operated: you will go through the basics of quantum algorithms, quantum error-correction, micro-architectures, compilers, and programming languages for quantum computing, and protocols for the quantum internet.

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• Self Paced
• English

Computational Thinking & Block Programming in K-12 Education

In the 21st century, computational thinking is a skill critical for all the world's citizens. Computing and technology is impacting all our lives and everyone needs to know how to formulate problems and express their solutions such that a computer can carry it out. In this Specialization you will both learn several block-based languages, but using novel approaches designed to make learning programming easier. Covers most CSTA Algorithms & Programming Standards for Algorithms, Variables, Control, and Modularity: Levels 1-3A.

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• Self Paced
• English

Digital Signal Processing

This Specialization provides a full course in Digital Signal Processing, with a focus on audio processing and data transmission. You will start from the basic concepts of discrete-time signals and proceed to learn how to analyze data via the Fourier transform, how to manipulate data via digital filters and how to convert analog signals into digital format. Finally, you will also discover how to implement real-time DSP algorithms on a general-purpose microcontroller.

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• Self Paced
• English

Java Programming and Software Engineering Fundamentals

Take your first step towards a career in software development with this introduction to Java—one of the most in-demand programming languages and the foundation of the Android operating system. Designed for beginners, this Specialization will teach you core programming concepts and equip you to write programs to solve complex problems. In addition, you will gain the foundational skills a software engineer needs to solve real-world problems, from designing algorithms to testing and debugging your programs.

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• Self Paced
• English

IBM Introduction to Machine Learning

Machine learning skills are becoming more and more essential in the modern job market. In 2019, Machine Learning Engineer was ranked as the #1 job in the United States, based on the incredible 344% growth of job openings in the field between 2015 to 2018, and the role’s average base salary of $146,085 (Indeed). This four-course Specialization will help you gain the introductory skills to succeed in an in-demand career in machine learning and data science.

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• Self Paced
• English

Digital Marketing and Data Driven Analytics

Digital Marketing is the backbone element which uses platforms and digital technologies, such as any kind of device to maintain connected to the users. Once the users are part of this ecosystem, the companies convert this random data in accurate algorithms to improve the effectiveness of any marketing campaign.

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• Self Paced
• English

Principles of Data Science Ethics

Concern about the harmful effects of machine learning algorithms and AI models (bias and more) has resulted in greater attention to the fundamentals of data ethics.

This data science ethics course for both practitioners and managers provides guidance and practical tools to build better models and avoid these problems. The course offers a framework data scientists can use to develop their projects and an audit process to follow in reviewing them. Case studies with Python code are provided.

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• Self Paced
• English

PyTorch Basics for Machine Learning

This course is the first part in a two part course and will teach you the fundamentals of PyTorch. In this course you will implement classic machine learning algorithms, focusing on how PyTorch creates and optimizes models. You will quickly iterate through different aspects of PyTorch giving you strong foundations and all the prerequisites you need before you build deep learning models.

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• Self Paced
• English

Accounting Data Analytics

This specialization develops learners’ analytics mindset and knowledge of data analytics tools and techniques. Specifically, this specialization develops learners' analytics skills by first introducing an analytic mindset, data preparation, visualization, and analysis using Excel. Next, this specialization develops learners' skills of using Python for data preparation, data visualization, data analysis, and data interpretation and the ability to apply these skills to issues relevant to accounting.

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• Self Paced
• English

IBM Machine Learning

Prepare for a career in the field of machine learning. In this program, you’ll learn in-demand skills like AI and Machine Learning to get job-ready in less than 3 months. Machine Learning is the use and development of computer systems that are able to learn and adapt by using algorithms and statistical models to analyze and draw inferences from patterns in data. Machine Learning is a branch of Artificial Intelligence (AI) where computers are taught to imitate human intelligence in that they solve complex tasks.

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• Self Paced
• English

Informed Clinical Decision Making using Deep Learning

This specialisation is for learners with experience in programming that are interested in expanding their skills in applying deep learning in Electronic Health Records and with a focus on how to translate their models into Clinical Decision Support Systems. The main areas that would explore are: Data mining of Clinical Databases: Ethics, MIMIC III database, International Classification of Disease System and definition of common clinical outcomes.

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• Self Paced
• English

CertNexus Certified Artificial Intelligence Practitioner

The Certified Artificial Intelligence Practitioner™ (CAIP) specialization prepares learners to earn an industry validated certification which will differentiate themselves from other job candidates and demonstrate proficiency in the concepts of Artificial intelligence (AI) and machine learning (ML) found in CAIP. AI and ML have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services.

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• Self Paced
• English

Big Data Fundamentals

Learn how big data is driving organisational change and essential analytical tools and techniques, including data mining and PageRank algorithms.

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• English

Algorithms and Data Structures Capstone

Synthesize your knowledge of algorithms and biology to build your own software for solving a biological challenge.

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• Self Paced
• English

Graph Algorithms in Genome Sequencing

Learn how graphs are used to assemble millions of pieces of DNA into a contiguous genome and use these genomes to construct a Tree of Life.

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• Self Paced
• English

String Processing and Pattern Matching Algorithms

Learn about pattern matching and string processing algorithms and how they apply to interesting applications.

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• Self Paced
• English

Graph Algorithms

Learn how to use algorithms to explore graphs, compute shortest distance, min spanning tree, and connected components.

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• Self Paced
• English

Algorithmic Design and Techniques

Learn how to design algorithms, solve computational problems and implement solutions efficiently.

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• Self Paced
• 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

Essentials of Genomics and Biomedical Informatics

This course presents clinicians and digital health enthusiasts with an overview of the data revolution in medicine and how to exploit it for research and in the clinic. The course will not make you a bioinformatician but will introduce the main concepts, tools, algorithms, and databases in this field.

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• English

Data Structures & Algorithms III: AVL and 2-4 Trees, Divide and Conquer Algorithms

Learn more complex tree data structures, AVL and (2-4) trees. Investigate the balancing techniques found in both tree types. Implement these techniques in AVL operations. Explore sorting algorithms with simple iterative sorts, followed by Divide and Conquer algorithms. Use the course visualizations to understand the performance.

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• Self Paced
• English

Data Structures & Algorithms II: Binary Trees, Heaps, SkipLists and HashMaps

Become familiar with nonlinear and hierarchical data structures. Study various tree structures: Binary Trees, BSTs and Heaps. Understand tree operations and algorithms. Learn and implement HashMaps that utilize key-value pairs to store data. Explore probabilistic data structures like SkipLists. Course tools help visualize the structures and performance.

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• Self Paced
• English

Data Structures & Algorithms I: ArrayLists, LinkedLists, Stacks and Queues

Work with the principles of data storage in Arrays, ArrayLists & LinkedList nodes. Understand their operations and performance with visualizations. Implement low-level linear, linked data structures with recursive methods, and explore their edge cases. Extend these structures to the Abstract Data Types, Stacks, Queues and Deques.

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• Self Paced
• English

Computing in Python IV: Objects & Algorithms

Learn about recursion, search and sort algorithms, and object-oriented programming in Python.

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• Self Paced
• English

Autonomous Mobile Robots

Basic concepts and algorithms for locomotion, perception, and intelligent navigation.

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• Self Paced
• English