What is Deep Learning Course?
Deep Learning is a cutting-edge branch of Artificial Intelligence that powers technologies like facial recognition, self-driving cars, and advanced natural language processing. As businesses increasingly adopt AI-driven solutions, understanding the principles and applications of Deep Learning has become essential for professionals looking to stay ahead in the rapidly evolving tech landscape.
Proficiency in Deep Learning is vital for professionals in fields such as data science, software development, business analysis, and IT management. Mastering this subject enables individuals to design and implement intelligent systems that drive innovation, improve efficiency, and enhance decision-making processes in their respective industries. Delegates seeking to future-proof their careers will greatly benefit from this training.
This 1-day course offered by Oakwood International provides a comprehensive introduction to Deep Learning concepts, tools, and techniques. Delegates will gain practical insights into building neural networks, understanding machine learning algorithms, and applying these skills to real-world problems. By the end of the course, delegates will feel confident in leveraging Deep Learning for impactful results in their organisations.
Course Objectives:
- To understand the fundamentals of Deep Learning and its role in AI
- To explore neural networks and their architectures
- To learn how to train and optimise Deep Learning models
- To interpret and evaluate Deep Learning models
- To apply Deep Learning techniques to solve real-worl challenges
- To develop problem-solving strategies using AI-powered systems
- To gain experience through practical exercises
Upon completing this course, delegates will receive a certification of achievement, recognising their foundational knowledge and practical skills in Deep Learning. This certification enhances professional credibility and demonstrates a commitment to continuous learning in AI.
Course Outline
Deep Learning Course
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
- 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
Included
Included
- No course includes are available.
Offered In This Course:
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Video Content
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eLearning Materials
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Study Resources
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Completion Certificate
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Tutor Support
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Interactive Quizzes
Learning Options
Discover a range of flexible learning options designed to meet your needs. Select the format that best supports your personal growth and goals.
Online Instructor-Led Training
- Live virtual classes led by experienced trainers, offering real-time interaction and guidance for optimal learning outcomes.
Online Self-Paced Training
- Flexible learning at your own pace, with access to comprehensive course materials and resources available anytime, anywhere.
Build your future with Oakwood International
We empower you with the skills, knowledge, and confidence to excel in your career. Join us and take the first step towards realising your professional goals.
Frequently Asked Questions
Q. What is deep learning, and how does it differ from machine learning?
Q. Who is this course designed for?
This course is ideal for data scientists, software developers, business analysts, IT professionals, and anyone keen to learn about advanced AI techniques.
Q. What will I learn in this course?
Key topics include neural networks, convolutional and recurrent neural networks, training models, deep learning frameworks, and practical applications.
Q. Is this course beginner-friendly?
Q. What career opportunities does this course offer?
Completing this course can lead to roles in AI engineering, data science, software development, and research.