Keras – Use in AI Course

Course Overview

Keras – Use in AI is an in-depth 8-week course tailored for M.Tech, M.Sc, and MCA students, as well as professionals in IT and related fields. This course is designed for individuals eager to explore neural networks and their applications using the Keras library. Participants will learn to build, train, and deploy deep learning models efficiently, applying these techniques to real-world AI projects such as image recognition and time series analysis.

Course Goals

The primary goal of this course is to provide participants with a comprehensive understanding of Keras as a powerful tool for developing advanced neural network models. By focusing on practical applications and deep learning techniques, participants will enhance their capabilities in AI model deployment.

Program Objectives

• Mastering Keras: Gain a comprehensive understanding of Keras for building and deploying neural network models.
• Practical Application Skills: Develop hands-on skills in configuring, training, and optimizing deep learning models using Keras.
• Innovative Problem Solving: Enhance problem-solving abilities by applying advanced AI techniques in real-world scenarios.

Program Structure

• Module 1: Introduction to Keras and AI
  • Overview of Keras and its role in AI development
  • Setting up and configuring Keras
  • Building your first Keras model
• Module 2: Core Concepts of Neural Networks in Keras
  • Basics of neural networks: layers, architectures, and Keras APIs
  • Understanding activation functions, loss functions, and optimizers in Keras
• Module 3: Practical AI Projects with Keras
  • Hands-on projects: building Convolutional Neural Networks (CNNs) for image recognition
  • Implementing Recurrent Neural Networks (RNNs) for time series analysis
  • Techniques for improving model performance and training efficiency
• Module 4: Advanced Techniques and Strategies in Keras
  • Using callbacks, checkpoints, and advanced configurations in Keras
  • Optimizing model deployment and ensuring scalability
• Module 5: Integrating AI into Business Solutions
  • Applying AI in industries like retail and healthcare
  • Ethical considerations and future trends in AI with Keras

Eligibility

• Students: M.Tech, M.Sc, MCA students with a background in AI, data science, or related fields.
• Professionals: E0 & E1 level professionals looking to enhance their deep learning skills with Keras.

Learning Outcomes

• Advanced Keras Skills: Master the use of Keras for developing and deploying AI models.
• Strategic AI Implementation: Gain the ability to strategically apply Keras models to solve complex real-world problems.
• Leadership in AI: Be prepared to lead AI-driven projects and initiatives using Keras.