Deep Learning Course in Fort McMurray

Deep Learning Course Outline

Module 1: Machine Learning Basics

• What is Machine Learning?
• Need for Machine Learning
• Types of Machine Learning

Module 2: Introduction to Deep Learning

• Importance of Deep Learning
• How Deep Learning Works?
• Difference Between Deep Learning and Machine Learning

Module 3: Artificial Neural Network

• Introduction
• Characteristics of Artificial Neural Network

Module 4: Deep Neural Networks

• Feedforward Networks
• Convolutional Neural Networks
• Recurrent Neural Networks

Module 5: Linear Algebra

• Mathematical Objects
• Computational Rules in Linear Algebra
• Matrix Multiplication Properties

Module 6: Probability

• Terminology
• Random Variables
• Probability Distributions
• Marginal Probability
• Conditional Probability
• Chain Rule of Conditional Probabilities
• Baye’s Rule

Module 7: Auto Encoders

• Need of Auto Encoder
• Architecture of Auto Encoders
• Applications of Auto Encoders

Module 8: Computational Graphs

• What are Computational Graphs?

Module 9: Monte Carlo Methods

• Introduction
• Machine Learning in Monte Carlo Method

Module 10: Deep Generative Models

• Introduction
• Boltzmann Machines
• Functioning of Boltzmann Machines

Module 11: Deep Learning Applications

• Applications of Deep Learning

Module 12: Libraries and Frameworks

• Libraries
• Framework
• Features of Deep Learning Framework

Who should attend this Deep Learning Course?

This Deep Learning Training Course aims at equipping individuals with knowledge of Natural Language Processing, Robotics, and even Healthcare. This course will teach Deep Learning algorithms, technologies, and applications providing delegates the skills needed to implement and adapt Deep Learning models for different tasks. This course can be beneficial for a wide range of professionals, including:

• Data Scientists
• Machine Learning Engineers
• Research Scientists
• Software Developers
• Artificial Intelligence (AI)/Machine Learning (ML) Product Managers
• Business Analysts
• Finance Professionals

Prerequisites of the Deep Learning Course

To attend this Deep Learning Training Course, delegates should have a basic understanding of Python, Linear Algebra, and Probability.

Deep Learning Course Overview

Deep Learning is a subset of Artificial Intelligence (AI) that focuses on algorithms inspired by the structure and function of the human brain's neural networks. It's pivotal in revolutionising industries like healthcare, finance, and technology by enabling machines to learn from data, recognise patterns, and make intelligent decisions autonomously.

Proficiency in Deep Learning Course is crucial for Data Scientists, AI Engineers, Software Developers, and Researchers. Mastering this field empowers professionals to create innovative image and speech recognition solutions, natural language processing, autonomous vehicles, and predictive analytics. It is essential for those aiming to stay competitive and drive technological advancements across various industries.

This intensive 1-day Deep Learning Training equips delegates with fundamental concepts and practical skills in deep learning. Through hands-on workshops and expert-led sessions, delegates comprehensively understand neural networks, convolutional and recurrent neural networks, and their applications. Delegates learn to implement deep learning models, interpret results, and optimise algorithms for diverse real-world scenarios.

Course Objectives

• To understand the foundational principles of neural networks
• To explore various deep learning architectures, including CNNs and RNNs
• To apply Deep Learning algorithms in image and speech recognition tasks
• To analyse and interpret profound learning model results effectively
• To optimise and fine-tune neural networks for improved performance
• To comprehend ethical considerations in deploying deep learning solutions
• To develop practical skills through hands-on exercises and case studies
• To foster confidence in applying deep learning techniques in real-world projects

After completing the Deep Learning Training, delegates receive a certification validating their proficiency in deep learning fundamentals. This certification attests to their understanding of neural network concepts, ability to design and implement deep learning models, and skills in utilising these techniques to solve practical problems effectively.

What’s included in this Deep Learning Course?

• World-Class Training Sessions from Experienced Instructors
• Deep Learning Certificate
• Digital Delegate Pack