e-Masters in Computer Science Artificial Intelligence and Machine Learning

• No Gate Score: Selection on academic and professional background
• High Impact Learning: Unique learning by doing pedagogy with 1:1 mentoring and visiting the IIIT Hyderabad campus.
• Executive Friendly: Weekend-only LIVE interactive sessions coupled with self-paced learning through best-in-class instructional materials.
• Career Access: Placement, startup incubation, and career advancement support.
• IIIT-H Alumni Status: Be a part of the prestigious IIIT Hyderabad alumni network with access to all the alumni privileges.

The program is ideal for professionals interested in building tech expertise and enhancing their careers. Applicants must have

• Minimum 1 year of work experience
• Bachelor's Degree (4 years program) or a Masters Degree with at least 50% marks or 5/10 CGPA
• Bachelor’s Degree (3-year program) with at least 50% marks or 5/10 CGPA may be considered based on relevant experience

The program will be taught by globally recognized academicians and research experts at IIIT Hyderabad. Meet your future mentors here.

Semester 1

Computer Science Principles

• Algorithms, Data Representation
• Functions, Branching
• Loops, Strings
• Lists, References and Memory
• Recursion, Searching Algorithms
• Runtime and Big-O Notation, Designing Efficient Algorithms (Dictionaries)
• Trees, Graphs
• Tree based search Algorithms, Graph based Search Algorithms

Computer Science for Data

• Simulation- Model, view, controller
• Levels of Concurrency, Pipelining
• Parallel Programming, Map Reduce
• How internet works, Authentication, Encryption
• Parsing, Modeling
• ML Models, ML Problem Formulation
• Data Analysis- Analyzing and Visualizing, Simulation- Experiments and Trials
• Tree Search, Heuristic Search

Database Management Systems

• Intro to DBMS & ER Models, Relational Models
• ER to Relational Models, Intro to SQL
• Fun with SQL - 1, Fun with SQL - 2
• SQL Joins, Storage: Disks & Buffers
• Storage: Files, Indexing
• Transaction Management: concurrency, Locking
• Schema Refinement, Normal Forms
• Normalization & Schema Refinement in DB design, Query optimization

Semester 2

Object Oriented Programming (OOP)

• High Level Programming Languages, Setting up class paths and environmental variables
• Java Code Dissection: Core Elements, Objects
• Java Code Dissection: Access Specifiers and Methods, Type Casting
• Encapsulation, Conditionals and Loops
• Recursion, Handling Exceptions and Errors
• Libraries, Inheritance
• Polymorphism, Analysis of Algorithms
• ADT and Dynamic Arrays, Single Linked List

Data Structures

• Selection and Insertion Sorting, Merge Sort and Quick Sort
• Double Linked List, Interfaces and Iterators
• Stack ADT, Queue ADT
• Priority Queue, Heaps, Heap Sort
• Binary Tree, Binary Search Tree
• Balance Binary Search Tree, SET and MAPS
• Hashing and Hash Tables, Handling Collisions in hashtable
• Graphs: Representations, Traversals

Principles of Software Engineering

• Testing and Object Methods in Java, Behavioral subtyping
• Delegation; Inheritance; Intro to Design Patterns, Design Patterns for reuse
• Domain Modeling, Intro to concurrency and GUIs
• Design Case study: Java Swings, Collections
• Libraries & Framework, Teams & Branch-based development and Workflows
• API: Process and Naming, Principles
• Concurrency: Java Primitives, Safety
• Software Development Process: Agile, Scrum

Semester 3

Computer Systems - I

• Bits Bytes and Integers: information Storage, Integer Representations
• Bits Bytes and Integers: Integer Arithmetic, Floating Point Representations
• History of Intel Processors & architectures, Machine Programming: Accessing Information
• Machine Programming: Arithmetic & Logical Operations, Control & Programming
• Machine Programming: Procedures, Buffer Overflow Attacks
• Cache Memory: Storage Technologies, Memory Hierarchy
• Cache Memory: Cache Memories, Building Cache
• Cache Memory: Implementing LRU Cache with misses, hits, and evicts, Impact of Cache on Program Performance

Computer Systems - II

• Introduction to Web Server, Implementing Client Server Model
• Delivering Static Content, Directory browsing
• Inter Process Communication, Fork and Exec
• Delivering Dynamic Content - Executing python, java programs
• Delivering Dynamic Content - Executing shell commands, Handling timeouts
• Adding Concurrency using Multi Threading, Multi Processing
• Running A/B testing on Multi Threading, Processing
• Proxy Server Implementation, Testing Proxy Server

Algorithms

• Tractibility, P vs NP
• Complete Search, Divide and Conquer
• Greeedy, Dynamic Programing
• Graphs: MST, Shortest Paths
• Network flow, Special Graphs
• Algorithms on Polygon with Libraries, String Matching Algorithms
• String Processing with Dynamic Programming, Tries
• Emerging Technology: Seminar Course

Semester 4

In the 4th semester, you will have the electives that are tailored to complement your specialization.

AI and Machine Learning Specialization Modules

• Programming, Math Foundations and Classical Algorithms
• Problem Formulation and Neural Networks
• Deep Learning
• Advanced Topics

• Get an Online Masters from IIIT Hyderabad
• Learn from a world-class faculty group drawn from IIIT Hyderabad
• Become a part of IIIT Hyderabad’s alumni network
• Develop practical skills in software development
• Get insights on Emerging Technologies
• Learn design thinking approach to solve complex problems