Accreditation:
EQF7
MaltaSwitzerlandWisconsinCaliforniaWashington
Workload:
2250 hours | 90 ECTS
Tuition cost:
1,80,000 INR

Master of Science in Computer Science: Artificial Intelligence and Machine Learning

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Kind
Degree
Area
Computer & Mathematical Science
Mode
Fully Online
Language
English
Student education requirement
Undergraduate (Bachelor’s)
Standard length
18 months
Standard delivery length
18 months
Certificates
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\ Overview

The course teaches students comprehensive and specialised subjects in computer science; it teaches students cutting edge engineering skills to solve real-world problems using computational thinking and tools, as well as soft skills in communication, collaboration, and project management that enable students to succeed in real-world business environments. Most of this program is case (or) project-based where students learn by solving real-world problems end to end. This program has core courses that focus on computational thinking and problems solving from first principles. The core courses are followed by specialization courses that teach various aspects of building real-world systems. This is followed by more advanced courses that focus on research level topics, which cover state of the art methods. The program also has a capstone project at the end, wherein students can either work on building end to end solutions to real world problems (or) work on a research topic. The program also focuses on teaching the students the “ability to learn” so that they can be lifelong learners constantly upgrading their skills. Students can choose from a spectrum of courses to specialize in a specific sub-area of Computer Science like Artificial Intelligence and Machine Learning, Cloud Computing, Software Engineering, or Data Science, etc.

125 hours | 5 ECTS
Introduction to Computer Programming: Part 1
125 hours | 5 ECTS
Relational Databases
125 hours | 5 ECTS
Introduction to Problem-Solving Techniques: Part 1
125 hours | 5 ECTS
Numerical Programming in Python
125 hours | 5 ECTS
Applied Statistics
125 hours | 5 ECTS
Introduction to Machine Learning
125 hours | 5 ECTS
Advanced Machine Learning
125 hours | 5 ECTS
Introduction to Deep Learning
125 hours | 5 ECTS
Deep Learning for Computer Vision
125 hours | 5 ECTS
Deep Learning for Natural Language Processing
125 hours | 5 ECTS
Productionization of ML Systems
125 hours | 5 ECTS
Distributed Machine Learning
750 hours | 30 ECTS
Advanced Applied Computer Science

\ Intended learning outcomes

Knowledge
Knowledge acquired by the learner at the end of the course:
- Define and explain core concepts in Artificial Intelligence, such as natural language processing, deep learning, and reinforcement learning - Analyze and critically evaluate the strengths and weaknesses of different machine learning algorithms - Compare and contrast various search techniques used in Artificial Intelligence
Skills
Skills acquired by the learner at the end of the course:
- Implement and apply machine learning algorithms in Python to solve real- world problems - Design and develop a simple neural network architecture for image recognition - Troubleshoot and debug errors encountered while working with machine learning models
Competencies
Competencies acquired by the learner at the end of the course:
- Formulate and solve a research question related to Artificial Intelligence or Machine Learning, and design a methodology to investigate it - Communicate and advocate the findings of the research project to a technical and non-technical audience - Adapt and innovate existing machine learning techniques to solve novel problems in different domains

Are you ready to take the next step towards your academic success?

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