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C programming Language

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Course offered by Venkata Maheswararao

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📘 C Programming Language – Course Content

🔹 Module 1: Introduction to Programming & C

  • What is programming?

  • History and features of C

  • Structure of a C program

  • Compilers and IDE setup (GCC, CodeBlocks, VS Code)

  • Writing and executing first C program


🔹 Module 2: Basics of C

  • Variables and data types

    • int, float, char, double

  • Constants and literals

  • Input/Output functions

    • printf(), scanf()

  • Operators

    • Arithmetic, relational, logical, assignment


🔹 Module 3: Control Structures

  • Decision making

    • if, if-else, nested if

    • switch-case

  • Loops

    • for, while, do-while

  • Break, continue, goto


🔹 Module 4: Functions

  • Function definition and declaration

  • Function types

  • Call by value vs call by reference

  • Recursion

  • Inline functions (concept)


🔹 Module 5: Arrays

  • One-dimensional arrays

  • Multi-dimensional arrays

  • String handling

  • Array operations (searching, sorting)


🔹 Module 6: Pointers (Core Strength of C)

  • Introduction to pointers

  • Pointer arithmetic

  • Pointers and arrays

  • Pointers and functions

  • Double pointers


🔹 Module 7: Strings

  • String functions (strlen, strcpy, strcmp)

  • String manipulation

  • Custom string functions


🔹 Module 8: Structures & Unions

  • Defining structures

  • Nested structures

  • Arrays of structures

  • Pointers to structures

  • Unions

  • typedef


🔹 Module 9: File Handling

  • File operations

    • fopen, fclose

    • fread, fwrite

    • fprintf, fscanf

  • Text vs binary files

  • Error handling in files


🔹 Module 10: Dynamic Memory Allocation

  • malloc(), calloc(), realloc(), free()

  • Memory management concepts

  • Memory leaks


🔹 Module 11: Preprocessor Directives

  • Macros

  • Header files

  • #define, #include, #ifdef

  • Conditional compilation


🔹 Module 12: Advanced Concepts

  • Command line arguments

  • Bitwise operators

  • Enum

  • Volatile and const keywords

  • Debugging techniques


🔹 Module 13: Data Structures in C (Intro)

  • Linked Lists

  • Stack

  • Queue

  • Basic trees (concept)


🔹 Module 14: Problem Solving & Algorithms

  • Searching algorithms

  • Sorting algorithms (Bubble, Selection, Insertion)

  • Time complexity basics


🔹 Module 15: Projects

  • Student Management System

  • Banking System

  • File-based record system

  • Mini compiler concepts (basic)


🎯 Learning Outcomes

  • Strong foundation in programming logic

  • Mastery of memory management and pointers

  • Ability to write efficient, optimized code

  • Understanding of low-level system concepts

About the Trainer

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Venkata Maheswararao

Phd in AI and ML from Nirwan University (in progress) - Master of Engineering - Master of Technology (M.E./M.Tech.) from Acharya Nagarjuna University in 2011 -Bachelor of Technology (B.Tech.) from Acharya Nagarjuna University in 1995 and

10 Years of Experience

I am a Serial Entrepreneur, Co-Founder, Chief Architect, and CEO of Adrevu.com, Softrevu.com, Couponsnagar.com, and Mahesys.com, specializing in AI/ML-powered affiliate marketing platforms, generative AI automation, quantitative trading systems, and enterprise technology innovation.

With extensive experience in building scalable digital ecosystems, I focus on integrating artificial intelligence, machine learning, and automation into marketing platforms, trading infrastructure, and enterprise solutions.

Global Affiliate Marketing Ecosystem

I collaborate with 1,000+ global brands through leading affiliate networks including:

Rakuten Marketing

Impact.com

Partnerize

Cuelinks

Avangate / 2Checkout (Verifone)

Through these partnerships, I help publishers scale traffic, revenue, and conversions by building intelligent affiliate marketing ecosystems powered by data, automation, and AI-driven insights.

AI / Generative AI Innovation

My work focuses heavily on building next-generation AI and Generative AI systems that enhance marketing intelligence and automation.

Key initiatives include:

Developing AI-driven marketing engines for personalization, coupon intelligence, and recommendation systems

Architecting conversational AI chatbots and automated customer engagement workflows

Building dynamic GenAI automation systems for marketing operations

Integrating LLM-based decision intelligence into marketing analytics and enterprise workflows

Quantitative Trading & Decision Support Systems (DSS)

I am currently architecting a proprietary AI-driven multi-strategy Decision Support System (DSS) designed for advanced quantitative trading.

Key components of the system include:

Multi-timeframe signal validation

Risk-governed execution and drawdown control

TradingView-to-MT5 automated execution pipelines

LLM / Generative AI reasoning with weighted score models

Strategy engines based on

Heikin Ashi

Renko

Quantitative Machine Learning (QML)

Breakout and momentum strategies

As part of this research and development, I have filed three provisional patents related to AI-based trading decision systems and risk-governed execution frameworks.

Enterprise Technology, AR & Cloud Innovation

I also work on enterprise technology initiatives involving:

Augmented Reality (AR) solutions for enterprise troubleshooting and maintenance workflows

Cloud-native platforms for scalable AI and automation systems

Machine learning–driven enterprise applications that improve operational intelligence and automation

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