4 Day Instructor-led

Overview

Learn How to Design, Build, and Deploy Deep Learning Models from scratch.

• There is a technological revolution happening, changing all aspects of our daily lives. AI (Artificial Intelligence) has penetrated deep into our activities, interactions, professions, comforts, and experiences.
• Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans: learn by example. Deep learning is a key technology behind autonomous vehicles, enabling them to recognize a stop sign or to distinguish a pedestrian from a lamppost. It is the key to voice control in consumer devices like phones, tablets, TVs, and hands-free speakers. Deep learning is getting lots of attention lately and for good reason. It’s achieving results that were not possible before.
• With AI, through deep learning models, machines can learn to predict outcomes based on the information you have available today. The result of a well-architected model can achieve state-of-the-art accuracy that, when combined with human intelligence, will yield extraordinary outcomes.

In This Artifical Intelligence and Deep Leaning Course You Will: 

• Understand the field of Artificial Intelligence
• Be able to describe AI Modelling
• Learn about the countless practical applications of AI
• Study how to build AI models using widely available tools
• Know the best practices to follow when working with AI

Audience Prerequisites

This course does not require any application development experience and is designed for the following categories of professionals:

• Data Scientists & Data Modelers
• Engineers interested in learning about and implementing AI-based solutions
• Developers and Application Team Leads
• Project and Program Managers
• Software Managers
• IT Operations Staff

Outline Of Topics

• Module 1: Introduction to the discipline of Artificial Intelligence (AI)
• Module 2: Introduction to Machine Learning (ML) and Deep Learning (DL)
• Module 3: Practical Applications of AI, ML, and DL
• Module 4: Practical Aspects of Deep Learning
• Module 5: AI Modelling- Defined
• Module 6: Selecting the correct Algorithm
• Module 7: Tuning AI Models
• Module 8: Foundations of Convolutional and Recurrent Neural Networks (CNN & RNN)
• Module 10: Introduction to Large Language Models (LLMs)