Duration: Four Days, Instructor-led

Overview

Building Deep Learning Models using Python

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.

In deep learning, a computer model learns to perform tasks directly from images, text, or sound. Deep learning models can achieve state-of-the-art accuracy that, especially when combined with experienced human intelligence, can lead to exceptional consistent results used by teams to make more informed decisions.

Deep Learning models are trained by using a large set of data and fed into neural network architectures that contain many visible and hidden layers of processing. This immersive deep learning course teaches you how to use this data to create outcomes to exponentially increase productivity.

During this four-day hands-on & immersive development workshop, you will learn how to build deep learning models from scratch using the Python programming language. You will learn how to use a multitude of proven techniques, with the help of widely used libraries, to prepare data from any source and use it to train deep learning model such that it is able to make reliable predictions.

In This Artificial Intelligence Course You Will: 

• Learn Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)
• Learn how to develop using the Python Programming Language
• Be able to process data from any source; local and remote; using Python
• Understand how to architect, build, and tune Deep Learning Models
• Know the best practices to follow

Audience Prerequisites

This developer focused deep learning course is designed for:

• Data Scientists & Modelers
• Engineers interested in learning how to develop DL models in Python
• Developers and Application Team Leads
• IT Operations Staff

Course Outline

Module 1: Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)

Module 2: Python Programming Basics

Module 3: Working with Python Libraries used with Deep Learning

Module 4: Architect and build Deep Learning models using Python

Module 5: Practical business-case for using Python to build DL models

Module 6: Tuning DL models

Module 7: Convolutional and Recurrent Neural Networks (CNN and RNN)Module 10: Working with Large Language Models (LLMs)