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Our Courses
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
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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
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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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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
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English
Autonomous Mobile Robots
Basic concepts and algorithms for locomotion, perception, and intelligent navigation.
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Self Paced
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English
Linear Algebra Basics
Machine learning and data science are the most popular topics of research nowadays. They are applied in all the areas of engineering and sciences. Various machine learning tools provide a data-driven solution to various real-life problems. Basic knowledge of linear algebra is necessary to develop new algorithms for machine learning and data science. In this course, you will learn about the mathematical concepts related to linear algebra, which include vector spaces, subspaces, linear span, basis, and dimension.
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21 hours
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English
Object-Oriented Programming in C++: Functions
This course is the third of five courses aiming to help you to become confident working in the object-oriented paradigm in the C++ language. This specialisation is for individuals who want to learn about objected oriented programming. It's an all-in-one package that will take you from the very fundamentals of C++, all the way to building a crypto-currency exchange platform. During the five courses, you will work with the instructor on a single project: a crypto-currency exchange platform.
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Self Paced
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10 hours
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English
Biology Meets Programming: Bioinformatics for Beginners
Are you interested in learning how to program (in Python) within a scientific setting? This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python.
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Self Paced
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19 hours
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English
Data Science Foundations: Data Structures and Algorithms
Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, searching, and indexing. …
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Self Paced
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English
Java FullStack Developer
Introducing the Java FullStack Developer Specialization, designed to empower your software development career by providing a comprehensive skillset for building integrated, cloud-ready web applications. The specialization consists of three intensive courses: Fundamentals of Java Programming: Understanding of core Java programming concepts and principles Proficiency in object-oriented programming principles such as inheritance, polymorphism, and abstraction Gaining knowledge in advanced Java topics like multi-threading, concurrency, and the application of common data structures Front-End for
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Self Paced
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English
Prediction and Control with Function Approximation
In this course, you will learn how to solve problems with large, high-dimensional, and potentially infinite state spaces. You will see that estimating value functions can be cast as a supervised learning problem---function approximation---allowing you to build agents that carefully balance generalization and discrimination in order to maximize reward. We will begin this journey by investigating how our policy evaluation or prediction methods like Monte Carlo and TD can be extended to the function approximation setting.
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22 hours
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English
Ethics in the Age of AI
As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations. In this specialization, we will explore the rise of algorithms, fundamental issues of fairness and bias in machine learning, and basic concepts involved in security and privacy of machine learning projects. We'll finish with a study of 3 projects that will allow you to put your new skills into action.
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Self Paced
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English
Accelerated Computer Science Fundamentals
Topics covered by this Specialization include basic object-oriented programming, the analysis of asymptotic algorithmic run times, and the implementation of basic data structures including arrays, hash tables, linked lists, trees, heaps and graphs, as well as algorithms for traversals, rebalancing and shortest paths. This Specialization sequence is designed to help prospective applicants prepare for the flexible and affordable Online Master of Computer Science (MCS) and MCS in Data Science.
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Self Paced
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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
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English
Modern Robotics, Course 3: Robot Dynamics
Do you want to know how robots work? Are you interested in robotics as a career? Are you willing to invest the effort to learn fundamental mathematical modeling techniques that are used in all subfields of robotics? If so, then the "Modern Robotics: Mechanics, Planning, and Control" specialization may be for you. This specialization, consisting of six short courses, is serious preparation for serious students who hope to work in the field of robotics or to undertake advanced study.
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Self Paced
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22 hours
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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
Recommender Systems
In this course you will: a) understand the basic concept of recommender systems. b) understand the Collaborative Filtering. c) understand the Recommender System with Deep Learning. d) understand the Further Issues of Recommender Systems. Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, conditional probability, and basic machine learning algorithms.
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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
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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
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English
Data Science Fundamentals
This specialization demystifies data science and familiarizes learners with key data science skills, techniques, and concepts. The course begins with foundational concepts such as analytics taxonomy, the Cross-Industry Standard Process for Data Mining, and data diagnostics, and then moves on to compare data science with classical statistical techniques.
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Self Paced
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English
Bioinformatics
Join Us in a Top 50 MOOC of All Time! How do we sequence and compare genomes? How do we identify the genetic basis for disease? How do we construct an evolutionary Tree of Life for all species on Earth? When you complete this Specialization, you will learn how to answer many questions in modern biology that have become inseparable from the computational approaches used to solve them.
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Self Paced
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English
AI Workflow: Machine Learning, Visual Recognition and NLP
This is the fourth course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. Course 4 covers the next stage of the workflow, setting up models and their associated data pipelines for a hypothetical streaming media company. The first topic covers the complex topic of evaluation metrics, where you will learn best practices for a number of different metrics including regressi
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Self Paced
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14 hours
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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
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English