Deep Learning Course at LearnAi

Master the Art of Neural Networks and AI

Why Enroll in the LearnAI Deep Learning Course?

Deep Learning, a subset of Machine Learning, is at the heart of groundbreaking advancements in artificial intelligence. From autonomous vehicles to voice recognition and healthcare diagnostics, Deep Learning is driving innovation across industries. At LearnAi, located in Dilsukhnagar, Hyderabad, our Deep Learning course is meticulously designed to provide you with the skills to build and optimize deep neural networks for real-world applications.

Our course offers a perfect blend of theoretical foundations and hands-on experience. You’ll dive into the architecture of neural networks, explore cutting-edge technologies, and gain proficiency in frameworks like TensorFlow and PyTorch. Whether you’re a data scientist, a tech enthusiast, or a professional aiming to specialize in AI, this course equips you with the expertise to create intelligent, adaptive systems.

Duration 30 Days

Deep Learning Course Online & Offline Classes

Mode of Training: Hybrid
Inclass & Online

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Who Should Enroll in the Deep Learning Course?

This course is ideal for individuals who want to become experts in designing, training, and deploying deep neural networks:

Beginners

Those with basic programming and machine learning knowledge who want to dive deeper into AI.

Deep Learning Course for Academic Student

Students

College and university students in fields like computer science, engineering, or data science aiming to specialize in AI.

Professionals

Software developers, data scientists, and IT professionals looking to advance their careers in AI and Deep Learning.

Deep Learning Course for Technology enthusiasts

Researchers

Academics and professionals aiming to explore innovative applications and contribute to AI research.

Deep Learning Course Curriculum

The Deep Learning Course follows a comprehensive and systematic curriculum. It includes the following core modules:

Fundamentals in C

Program
Programming
Programming Languages
Types of Software
Introduction to C
History of C
Features of C
Applications of C
Character Set, ASCII Table
Tokens
Keywords
Identifiers & Naming Rules
Constants
Data Types
Type Qualifiers
How Data is Stored in Computer Memory
Variables
Variable Declaration
Variable Assignment
Variable Initialization
Comments
Defining Constants

Input-Output Functions

Input-Output Library Functions
Non-Formatted Input and Output
Character-Oriented Library Functions
Compiler, Linker, and Loader
Program Execution Phases
Formatted Library Functions
Mathematical Library Functions
Structure of a C Program
IDE
Basic Programs

Arrays

Arrays
One-Dimensional Arrays
Declaration of 1D Arrays
Initialization of 1D Arrays
Accessing Elements of 1D Arrays
 Reading and Displaying Elements
 Programs on 1D Arrays
 Two-Dimensional Arrays
 Declaration of 2D Arrays
 Initialization of 2D Arrays
 Accessing Elements of 2D Arrays
 Reading and Displaying Elements
 Programs on 2D Arrays
 Three-Dimensional Arrays

Pointers

Understanding Memory Addresses
Pointer Operators
Pointer
Pointer Advantages and Disadvantages
Declaration of Pointer Variables
Initialization of Pointer Variables
 Dereferencing / Redirecting Pointer Variables
Declaration versus Redirection
Void Pointer
Null Pointer
Compatibility
Array of Pointers
Pointer to Pointer
Pointer Arithmetic
Dynamic Memory Allocation Functions

Storage Classes

Object Attributes
Scope
Extent
Linkage
auto
static
extern
register

Structures, Unions, Enumerations and Typedef

Structures
Structure Type Declaration
Structure Variable Declaration
Initialization of Structure
Accessing the Members of a Structure
Programs Using Structures
Operations on Structures (Copying and Comparing Structures)
Nested Structures (Complex Structures)
Structures Containing Arrays (Complex Structures)
Array of Structures (Complex Structures)
Pointer to Structure
Accessing Structure Member through Pointer Using Dynamic Memory Allocation
Pointers within Structures
Self-Referential Structures
Passing Structures to Functions
Functions Returning Structures
Unions
Differences between Structures & Unions
Enumerated Types / enum Keyword
The Type Definition / typedef Keyword
Bit Fields

Operators and Expressions

Arithmetic Operators
Arithmetic Expressions
Evaluation of Expressions
Relational Operators
Logical Operators
Assignment Operators
Increment & Decrement Operators
Conditional Operator
Bitwise Operators
Type Casting
Sizeof Operator
Comma Operator
Operators Precedence and Associativity
Expressions
Evaluation of Expressions

Control Statements

Conditional Control Statements
 if
 if-else
 Nested if-else
if-else-if Ladder
Multiple Branching Control Structure
 switch-case
 Loop Control Statements
 while
 do-while
for
 Nested Loops
 Jump Control Structures
 break
 continue
 goto
 return
 Programs

Strings

String Concept
 Introduction to Strings in C
 Storing Strings
 The String Delimiter
 String Literals (String Constants)
 Strings and Characters
 Declaring Strings
 Initializing Strings
Strings and the Assignment Operator
String Input Functions / Reading Strings
String Output Functions / Writing Strings
 String Input-Output using fscanf() and fprintf() Functions
 Single Character Library Functions / Character Manipulation in Strings
 String Manipulation Library Functions
Programs Using Character Arrays
 Array of Strings (2D Character Arrays)
 Programs Using Array of Strings

Functions

Functions
 Advantages of Using Functions
 Defining a Function
Calling a Function
 Return Statement
Function Prototype
 Basic Function Designs
 Programs Using Functions
 Scope
 Recursion
 Iteration vs Recursion
 Nested Functions
 Variable Length Number of Arguments
 Parameter Passing Techniques – Call by Value & Call by Address
 Functions Returning Pointers
 Pointers and One-Dimensional Arrays
 Pointers and Two-Dimensional Arrays
 Passing 1D Arrays to Functions
 Passing 2D Arrays to Functions
 Pointers and Strings
 Passing Strings to Functions
 Pointer to Function

Preprocessor Directives

The #include Preprocessor Directive & User Defined Header Files
The #define Preprocessor Directive: Symbolic Constants
The #define Preprocessor Directive: Macros
Conditional Compilation Directives
#if
 #else
 #elif
#endif
#ifdef
 #ifndef
#undef
 #error
 #line
#pragma

Course Overview

The LearnAi Deep Learning Course provides a structured and in-depth exploration of neural networks and their applications. You’ll start with the fundamentals of perceptrons, activation functions, and backpropagation, progressing to advanced concepts like convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs).

With a strong emphasis on practical learning, you’ll implement models for tasks like image classification, natural language processing, and time-series forecasting. Our industry-aligned projects and case studies will give you hands-on experience in solving real-world problems with Deep Learning.

Skills You Will Gain

Upon completing the Deep Learning Course, you will acquire a comprehensive skill set to excel in AI-driven fields:

Neural Network Design

Learn to design and implement deep neural networks from scratch.

ANN

Understand and neural networks layer for tasks like Regression and Classification

RNN

Understand and create Recurrent layer for tasks like text summarization and time series forecasting

CNN

Understand and create Convolutional layer for tasks like image and video analysis

Generative Models

Understand and create GANs for tasks like image generation and data augmentation.

Model Optimization

Master techniques like hyperparameter tuning, regularization, and dropout for better performance.

Learn Deep Learning Course from beginners to advanced in Three Phases

Our course progresses through beginner to advanced levels, starting with neural network basics and advancing to complex architectures and applications. Each phase includes interactive lectures, coding challenges, and project-based learning to ensure mastery.

1. Exploration

Industrial Standard Course Structure

Job Oriented Programs

Domain Expertise Trainers

Recording Sessions

24/7 Portal Access

1 to 1 Mentorship

2. Understanding

Doubt Sessions

Daily Assignments

Weekly Test

Project Explanations

Project Implementation

Course Completion Certifications

3. Achievement

Resume Preparations

Interview Preparation

Mock Interviews

Internships Oppurtunity

Resume Marketing

100% Job Assistance

Tools and Technologies

• TensorFlow
• Keras
• PyTorch
• OpenCV
• Python (NumPy, Pandas, Matplotlib)
• Google Colab and Jupyter Notebooks

Job Roles

• Deep Learning Engineer
• AI Research Scientist
• Data Scientist
• Computer Vision Specialist

• NLP Engineer
• AI Consultant
• Software Engineer (AI)

Join the Deep Learning Course at LearnAi and become proficient in building AI systems that transform industries. Take the next step in your AI journey today and shape the future with Deep Learning expertise!

FAQs

What is C programming?

 C is a high-level programming language known for its efficiency and control over hardware, widely used in system and application software development.

What are the main features of C programming?

C is praised for its simplicity, portability, efficiency, and capability for direct memory manipulation.

What are pointers in C, and why are they important?

Pointers are variables that store memory addresses, essential for dynamic memory management and efficient data handling.

How does C differ from C++?

C is a procedural language focused on functions, while C++ extends C with object-oriented features like classes and inheritance for more complex programming.

What makes LearnAI courses exceptional?

Our courses feature cutting-edge curricula, expert instructors, and hands-on projects that provide practical experience and real-world applicability.

How qualified are LearnAI instructors?

Our instructors are experienced professionals with extensive industry backgrounds, offering valuable insights and skills.

What kind of support do students receive?

Students benefit from personalized mentorship, detailed feedback, and extensive support throughout their learning process.

How does LearnAI support career growth?

 We offer career services including resume building, interview coaching, and job placement assistance to help you advance in your career.li>

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