Master of Science in Computer Science: Artificial Intelligence and Machine Learning
Scaler Neovarsity
Accreditation:
Tuition costs:
5,09,000 INR
Area:
Computer Science
Duration:
18 months
Language:
English
Mode:
Fully Online
Description:
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. Most of this program is the 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 problem 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 and Full Stack Development, etc.
Degree ILOs:
Degree structure
In total, Master of Science in Computer Science: Artificial Intelligence and Machine Learning is 2250 hours to complete; the programme is structured with tiers, which are described below.
Tier 1: Foundational Modules
375 required hours
Learners should complete 15 ECTS (3 courses) from Tier 1.
Relational Databases
Relational Databases
125h
Data Structures
Data Structures
125h
Design and Analysis of Algorithms
Design and Analysis of Algorithms
125h
Introduction to Computer Programming: Part 1
Introduction to Computer Programming: Part 1
125h
Introduction to Problem-Solving Techniques: Part 1
Introduction to Problem-Solving Techniques: Part 1
125h
Tier 2: Specialization in Artificial Intelligence and Machine Learning
1125 required hours
Learners should complete 45 ECTS (9 courses) from Tier 2
Productionization of Machine Learning (ML) systems
Productionization of Machine Learning (ML) systems
125h
Deep Learning for Computer Vision
Deep Learning for Computer Vision
125h
Deep Learning for Natural Language Processing (NLP)
Deep Learning for Natural Language Processing (NLP)
125h
Advanced Machine Learning
Advanced Machine Learning
250h
Distributed Machine Learning
Distributed Machine Learning
125h
Introduction to Deep Learning
Introduction to Deep Learning
125h
Introduction to Machine Learning
Introduction to Machine Learning
250h
Applied Statistics
Applied Statistics
125h
High Dimensional Data Analysis
High Dimensional Data Analysis
125h
Numerical Programming in Python
Numerical Programming in Python
125h
System Design
System Design
125h
DevOps
DevOps
125h
Tier 3: Electives
500 required hours
Learners should complete 20 ECTS (4 courses) courses
System Design
System Design
125h
Statistical Programming
Statistical Programming
125h
Introduction to Problem-Solving Techniques: Part 2
Introduction to Problem-Solving Techniques: Part 2
125h
Introduction to Computer Programming: Part 2
Introduction to Computer Programming: Part 2
125h
Front End UI/UX Development
Front End UI/UX Development
125h
JavaScript
JavaScript
125h
Front End Development
Front End Development
125h
Back End Development
Back End Development
125h
Foundations of Cloud Computing
Foundations of Cloud Computing
Advanced Back End Development
Advanced Back End Development
125h
Distributed Cloud Computing
Distributed Cloud Computing
NoSQL Cloud Datastores
NoSQL Cloud Datastores
Design Patterns
Design Patterns
125h
Advanced Algorithms
Advanced Algorithms
125h
Computer Systems and Their Fundamentals
Computer Systems and Their Fundamentals
125h
Low-Level Design and Design Patterns
Low-Level Design and Design Patterns
Practical Software Engineering
Practical Software Engineering
125h
Distributed Systems with High-Level System Design
Distributed Systems with High-Level System Design
Power BI for Data Analysis and Exploration
Power BI for Data Analysis and Exploration
Spreadsheets for Data Understanding
Spreadsheets for Data Understanding
Advanced Python Programming
Advanced Python Programming
Foundations of Machine Learning
Foundations of Machine Learning
125h
Business Case Studies
Business Case Studies
Studies in Data Science and Data Analytics
Studies in Data Science and Data Analytics
SQL for Data Analytics
SQL for Data Analytics
125h
Product Analytics
Product Analytics
125h
Data Visualisation Tools
Data Visualisation Tools
125h
Tier 3: Capstone
250 required hours
Learners should a complete 10 ECTS (1 courses) Capstone project.
