Deep Learning & Neural Networks

Course Ratings

"This deep learning course exceeded my expectations. The instructors explained complex neural network concepts in a clear, practical way. Building CNNs and transformers on real datasets was challenging but incredibly rewarding. I now feel confident applying deep learning in real projects and continuing to specialise in AI.”"

Deep Learning & Neural Networks Course

2 Days £575

About this Course

This course provides an in-depth exploration of deep learning, equipping learners with the knowledge and practical skills to build advanced AI systems. From the fundamentals of neural networks to convolutional and recurrent architectures, learners gain experience designing, training, and evaluating models for real-world applications. The course emphasises hands-on coding, real datasets, and industry-relevant techniques, preparing learners for careers in AI research, development, and specialised fields such as computer vision, natural language processing, and autonomous systems.

Course Content

Module 1: Neural Network Foundations
Learners begin by understanding the core principles behind neural networks, including perceptrons, activation functions, backpropagation, and optimisation algorithms. This module balances theory with practical exercises, allowing learners to build simple neural networks from scratch, visualise their behaviour, and appreciate the mathematics behind deep learning in a clear, accessible way.

Module 2: Advanced Architectures
This module explores modern neural network architectures such as convolutional neural networks (CNNs) for image processing, recurrent neural networks (RNNs) for sequential data, and transformers for natural language processing. Learners will implement these models using popular frameworks like TensorFlow and PyTorch, applying them to real-world datasets to gain hands-on experience with complex AI systems.

Module 3: Model Training & Optimisation
Focusing on making models work in practice, this module covers data preprocessing, loss functions, regularisation, hyperparameter tuning, and evaluation metrics. Learners also learn to detect and prevent overfitting, accelerate training with GPU optimisation, and implement strategies to improve model performance and reliability in production environments.

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Deep Learning & Neural Networks Course
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Who is This Deep Learning & Neural Networks Course For?

This course is designed for software developers, AI engineers, data scientists, and technically-minded professionals looking to specialise in deep learning. It is ideal for anyone seeking a deep, hands-on understanding of neural networks and modern AI techniques, from students and career changers to engineers looking to apply deep learning in professional projects.


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10th March 2026

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10th June 2026

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Why You Should Attend our Deep Learning & Neural Networks course

Learners who complete this course will leave with both theoretical understanding and practical experience in deep learning. The course equips participants to build, train, and deploy neural network models, tackle real-world AI problems, and confidently pursue advanced AI roles in research, enterprise, or specialised sectors like defence, robotics, and space applications.


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Why Choose Infinity AI Learning for Deep Learning & Neural Networks Training?

Infinity AI Learning provides highly practical, industry-focused AI training with a focus on real-world application. Led by expert instructors, our courses combine theory with hands-on practice using real datasets, AI frameworks, and professional workflows. Our learners gain skills that are immediately relevant, supported by guidance, mentorship, and access to a community of AI developers.


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