https://github.com/edaaydinea/micromaster-in-artificial-intelligence
This repository includes all the URLs about MicroMaster in Artificial Intelligence
https://github.com/edaaydinea/micromaster-in-artificial-intelligence
Last synced: 6 months ago
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This repository includes all the URLs about MicroMaster in Artificial Intelligence
- Host: GitHub
- URL: https://github.com/edaaydinea/micromaster-in-artificial-intelligence
- Owner: edaaydinea
- License: apache-2.0
- Created: 2022-10-20T13:33:48.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2022-11-06T21:15:20.000Z (almost 3 years ago)
- Last Synced: 2023-10-20T09:36:01.618Z (almost 2 years ago)
- Size: 934 KB
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# MicroMaster-in-Artificial-Intelligence
The ColumbiaX MicroMasters® Program in Artificial Intelligence is a professional and academic credential offered by edX.org for online learners. These Masters level courses include video lectures, quizzes, programming assignments, peer-reviewed assignments, and community discussion forums. Learners who successfully complete all courses in the MicroMasters program on edX receive a MicroMasters program certificate that they can share on their resume and LinkedIn.
Learners who successfully complete all four courses in the AI MicroMasters program and receive a certificate for each course, will earn an edX MicroMasters program certificate from ColumbiaX.
Recipients of a MicroMasters program certificate can apply to Columbia University's online or on-campus Masters in Computer Science program. If admitted, students will receive 7.5 course credits towards their MS in Computer Science degree. MicroMasters credits cannot be combined with any other transfer credits.
The 7.5 course credits are equivalent to the following:
COMS W4701 Artificial Intelligence (3 credits)
COMS W4771 Machine Learning (3 credits)
COMS W4901 Projects in Computer Science (1.5 credits)
Once formally approved, the courses can count toward any requirements/electives that fit the chosen MS track and, the first two courses (AI, ML) will count as part of the CS MS Breadth Requirement, specifically as two courses in Group 3 (AI and Applications). Students still must take one course from Group 1 (Systems), and one course from Group 2 (Theory) in order to satisfy the Breadth Requirement. Note that this requirement is common to all CS MS tracks that the student may choose. It is not tied to a single track.
Once formally approved, the last course (Projects in Computer Science) will count as part of the Elective Track Course Requirement. Note that this is common to all CS MS tracks.
The MicroMasters Program in Artificial Intelligence consists of four courses:
* [**CSMM101X - Artificial Intelligence**](https://github.com/edaaydinea/CSMM101X-Artificial-Intelligence)
* This course includes the fundamental concepts of Artificial Intelligence (AI) and apply them to the design and implementation of intelligent agents that solve real-world AI problems, including problems in search, games, machine learning, logic, and constraint satisfaction.
* Topics include the history of AI, intelligent agents, state-space problem representations, uninformed and heuristic search, game playing and adversarial search, logical agents, constraint satisfaction problems, along with techniques in machine learning and other applications of AI, such as natural language processing (NLP).
* [**Completion certificate**](ColumbiaX%20CSMM.101x%20Certificate%20_%20edX.pdf)
* [**CSMM102X - Machine Learning**](https://github.com/edaaydinea/CSMM102X-Machine-Learning)
* This course provides an introduction to supervised and unsupervised techniques for machine learning. We will cover both probabilistic and non-probabilistic approaches to machine learning. Focus will be on classification and regression models, clustering methods, matrix factorization and sequential models.
* Methods covered in this course include linear and logistic regression, support vector machines, boosting, K-means clustering, mixture models, expectation-maximization algorithm, hidden Markov models, among others. Please see the course outline below for a more detailed description of the contents of this course.
* [**Completion certificate**](ColumbiaX%20CSMM.102x%20Certificate%20_%20edX.pdf)
* [**CSMM103X - Robotics**](https://github.com/edaaydinea/CSMM103X-Robotics)
* Method covered in this course include introduction to ROS, 2D - 3D Transforms, Transforms Inverse,Transform in
ROS, Forward Kinematics, Analytical IK, Robot Workspaces, Differential Kinematics, Singularities, Full
Kinematics, Motion Planning, Stochastic Motion Planning, Mobile Robots, Mobile Robots Kinematics.
* [**Completion certificate**](ColumbiaX%20CSMM.103x%20Certificate%20_%20edX.pdf)
* [**CSMM104X - Animation and CGI Motion**](https://github.com/edaaydinea/CSMM104X-Animation-CGI-Motion)
* Method covered in this course include configuration space, velocity, state, Hamiltonian vector filed and flow,
forces, time integration, electron clouds, billiard balls, continuous time detection, iterated collision response,
geometric collision response, Broad phase collision detection, Rigid Body Kinematics/Dynamics/Collisions,
Elasticity, Fluids.
* [**Completion certificate**](ColumbiaX%20CSMM.104x%20Certificate%20_%20edX.pdf)
This program allows learners to gain expertise in one of the most fascinating and fastest growing areas of computer science through an innovative online program that covers fascinating and compelling topics in the field of Artificial Intelligence and its applications. This MicroMasters program will give you a rigorous, advanced, professional, graduate-level foundation in Artificial Intelligence.
