Basics - Introduction to GNU Tool chain, Linux environment and VI editor, Tokens of C - Keywords, Data-Types, Variables, Constants, Operators, Identifiers, Storage Class Specifiers, Control Flow Statements, GNU Make utility, Arrays, Multidimensional arrays, Data Input & Output, Strings, Loops - for, while etc., Functions and Recursion

Advanced - Pointers - Intro, Pointer Arithmetic, Pointers and Arrays, Pointers and Functions, Pointers and Strings, Structures, Unions, Enum, Typedef, Bit field operators and pointers with structures, Preprocessors, C and Assembly, Files, I/O, Variable No. of arguments, Command Line arguments, Error handling and debugging with GNU GDB, Memory layout, Calling Conventions - cdecl, std, fastcall, Format string problems, Stack Overflow, Buffer Overflow, Integer Overflows, Introduction to various C standards, Secure Coding in C - SEI CERT C coding standard

SDLC: Introduction to Secure SDLC, Threats, Vulnerability & Attack, What is software Security, Why threat modelling? How to threat model? STRIDE and mitigation techniques, Data Flow Diagrams & STRIDE, Microsoft Threat Modeling Tool, Attack Surface Analyser, Attack trees and Abuse cases

Introduction to Data Structures, Complexity of Algorithms - Space and time complexity, Linked Lists, Stacks, Queues, Sorting algorithms - Bubble, selection, insertion, quick, merge and heap sort, Searching algorithms - linear and binary search, Hashing - collision, collision resolution techniques, Trees - Binary trees, Binary search trees, AVL trees, Graphs - terminology, breadth first and depth first traversals, spanning trees, minimum spanning tree algorithms, shortest path algorithms, Pattern Matching algorithms, Pattern matching algorithms - Naive, Rabin-Karp, KMP & Boyer-Moore substring search algorithms

OS Organization, Architecture, Structure and Operations, Process Management - Processes, Threads, Concurrency, Process Synchronization, CPU Scheduling, Static and Shared Libraries, Memory Management -  Main Memory and Virtual Memory, Filesystem Management - File System interface, IPC mechanisms  - Pipes, Named Pipes, FIFOs, Message Queues, Mutexes, Condition Variables, Read Write locks, Semaphores, Shared Memory, Access Control Mechanisms - Discretionary Access Control & Mandatory Access Control

Network Programming: Introduction to TCP/IP Networking Stack , Socket Introduction, Elements of TCP sockets, TCP Client-Server, I/O Multiplexing (select/poll), Elements of UDP sockets, Non-blocking I/O & IOCTL operations

Computer Security Concepts, Networking Devices (Routers/Switches/Bridges), Security Attacks: Active & Passive, Introduction to Bug, Vulnerability, Threat, Attack, Exploit. Popular attacks launched by exploiting the vulnerabilities, Security Services - Authentication, Access Control, Data Confidentiality, Data Integrity, Non-Repudiation & Availability, Security Mechanisms, Classical Encryption - Cryptography, Cryptanalysis & Brute Force Attacks, Substitution & Transposition Techniques, Cryptographically strong random numbers/APIs, Introduction to Steganography, Denial of Service (DoS) Attacks & Distributed Denial of Service Attacks (DDoS), Stream Ciphers & Block Ciphers, Public Key Cryptography & RSA, Diffie-Hellman Key Exchange & Man-in-the-Middle Attack, Message Authentication Code (MAC), Hash Functions & Hashed Message Authentication Code (HMAC), Digital Signatures, Digital Certificates, X.509 & Public-key Infrastructure (PKI) Firewalls: Characteristics, Types, Bastion Host & Firewall Locations & Configurations, Intrusion Detection and Intrusion Prevention Systems, Signature Based/Flow Based/Anomaly Detection Based, Trustworthy Log Generation, Security Protocols - Pretty Good Privacy & S/MIME, VPN – IPSec,  Secure Sockets Layer (SSL) & Transport Layer Security (TLS) & DNS Security (DNSSEC)

Introduction - Object Oriented Programming and concepts, Java language and its features, JDK, JRE and JVM, Basic Programming Constructs - Charset, identifiers, data types, variables, constants, literals operators, decision making statements (if, switch), iterative statements (while, do, for and for-each), jump statements (break, continue and return) and keywords, Classes and Objects, Data and methods members - Types of variables and their scope, Creating objects, Constructors, Overloading, Parameter passing in Java, this and static keywords, JVM and Garbage Collection - Java Virtual Machine and subsystems, Class loading and Execution Engine systems, Java runtime memory system,

Inheritance and Polymorphism - Visibility modifiers, extends and super keywords, Abstract classes, Run-time polymorphism, Interfaces, Inner classes, Anonymous inner classes, Packages and Wrapper Classes - Importing  packaging, Defining custom packages, Wrapper classes, Modifiers in Java, Exception Handling - Introduction to exceptions – checked and unchecked, Java’s exception handling mechanism, Writing custom exceptions in Java, Arrays and Strings - Arrays, Strings, String constant pool, String comparison and methods, Stringbuffer and Stringbuilder classes, Command line arguments

IO Streams - Text Streams – Reader and Writer, Byte Streams – InputStream and OutputStream, File IO –Filereader and Filewriter , Processing Buffers, Ways of reading data from Keyboard, Multi-Threading- Concept of Thread and thread life cycle, Creating a thread, Thread class and its methods, Thread synchronization and inter thread communication

Java Collection Framework - Need of collections in Java, Key interfaces of Collection Framework – Collection, List, Set, Queue, Map, etc.,Legacy and non-legacy collection classes, Iterators and Enumerator, Utility classes – Collections and Arrays, Exploring java.util package – Date, Calendar, Scanner etc. Generic Programming in Java, Introduction, Writing a Generic Class, Passing Objects of a Generic Class to a Method, Writing Generic Methods, Constraining a Type Parameter in a Generic Class, Use of wildcards – upper and lower bounds, , Secure Coding in Java, SEI CERT Java coding standard, Design Patterns in Java

Mathematics for Machine Learning - Linear Algebra (Including Matrix Operations), Probability & Statistics, Python  libraries for Machine Learning (Numpy, Pandas, Matplotlib, Scikit-learn), Introduction to Supervised, Unsupervised and Semi-supervised Learning,  Data pre-processing & Feature engineering, Regression - Linear Regression, Multiple Linear Regression, Support Vector Machine (SVM), KNN,  Classification - Logistic regression, KNN, SVM, Decision Trees, Naive Bayes, Evaluation of Regression Models & Classification.