Neural Networks With Deep Learning Training Course in Columbia

Neural Networks with Deep Learning Training Course Outline

Module 1: Introduction to Neural Networks

• Introduction to Neural Networks
• Supervised Learning with Neural Networks

Module 2: Neural Networks Fundamentals

• Binary Classification
• Logistic Regression
• Gradient Descent and Derivatives
• Computational Graph
• Vectorisation
• Introduction to Python
• Jupyter/IPython Notebooks

Module 3: Shallow Neural Networks

• Representation of a Neural Networks
• Computing the Output of a Neural Network
• Vectorised Implementation
  • Feed Forward
  • Back Propagation
• Hidden Layer
• Activation Functions
• Gradient Descent for Neural Networks

Module 4: Deep Neural Networks

• Deep L-Layer Neural Network
• Forward Propagation
• Computational Graphs
• Backward Propagation
• Neural Networks Training
• Deep Representations
• Building Blocks
• Difference Between Parameters and Hyperparameters

Who should attend this Neural Networks with Deep Learning Training Course?

The Neural Networks with Deep Learning Course is designed for individuals working in data science, artificial intelligence, and related fields who wish to deepen their understanding and practical skills in deep learning. The following are some professionals for whom this course can be beneficial:

• Data Scientists
• AI Engineers
• Software Developers
• Machine Learning Engineers
• Researchers
• Analysts
• IT Professionals

Prerequisites of the Neural Networks with Deep Learning Training Course

There are no formal prerequisites for this Neural Networks with Deep Learning Course. However, a basic understanding of programming and familiarity with machine learning concepts would be beneficial.

Neural Networks with Deep Learning Training 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 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 course 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

Upon completing this course, delegates will have acquired the knowledge and skills necessary to implement and optimise deep learning models using TensorFlow, making them invaluable assets in their professional fields.

What’s included in this Neural Networks with Deep Learning Training Course?

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