Neural Networks & Deep Learning

Master the foundations of artificial intelligence and build sophisticated neural architectures that power modern AI applications

12 Weeks • Intermediate Level

Expert Instructors

Industry Projects

Course Overview

Dive deep into the world of neural networks and deep learning with this comprehensive course designed for aspiring AI engineers. Learn from industry experts who have built neural networks at scale for companies like Google, Facebook, and Tesla.

This hands-on program combines theoretical foundations with practical implementation, ensuring you understand both the mathematics behind neural networks and how to build production-ready deep learning systems.

Build from Scratch

Implement neural networks from first principles using NumPy before using advanced frameworks

Industry Frameworks

Master TensorFlow and PyTorch for building scalable deep learning applications

Real Projects

Work on industry-grade projects including image classification, speech recognition, and NLP

€2,499

Complete Course Package

Duration 12 Weeks

Format Online + Live Sessions

Level Intermediate

Projects 5 Capstone Projects

Certificate Industry Recognized

💳 Flexible payment plans available
🔄 30-day money-back guarantee

Course Curriculum

A comprehensive 12-week journey through neural networks and deep learning

Foundations of Neural Networks

Understanding the biological inspiration, mathematical foundations, and basic architecture of artificial neural networks.

• Perceptrons and multilayer networks
• Activation functions and their properties
• Forward propagation mechanics

• Loss functions and cost optimization
• Gradient descent algorithms
• Backpropagation from scratch

Week 1-2

Deep Learning Frameworks

Master TensorFlow and PyTorch for building scalable neural networks with automatic differentiation and GPU acceleration.

• TensorFlow 2.x ecosystem
• Keras high-level API
• PyTorch dynamic computation graphs

• GPU acceleration and CUDA
• Model serialization and deployment
• Performance optimization techniques

Week 3-4

Convolutional Neural Networks

Deep dive into CNNs for computer vision applications, including image classification, object detection, and segmentation.

• Convolution and pooling operations
• CNN architectures (LeNet, AlexNet, VGG)
• ResNet and skip connections

• Transfer learning strategies
• Data augmentation techniques
• Object detection with YOLO

Week 5-7

Recurrent Neural Networks

Explore sequence modeling with RNNs, LSTMs, and GRUs for natural language processing and time series analysis.

• Vanilla RNNs and vanishing gradients
• LSTM and GRU architectures
• Bidirectional and stacked RNNs

• Attention mechanisms
• Sequence-to-sequence models
• Time series forecasting

Week 8-9

Advanced Architectures & Applications

Cutting-edge neural network architectures including Transformers, GANs, and Autoencoders for various applications.

• Transformer architecture basics
• Generative Adversarial Networks
• Variational Autoencoders

• Neural style transfer
• Reinforcement learning basics
• Production deployment strategies

Week 10-12

Capstone Projects

Build industry-grade applications that showcase your neural network expertise

Medical Image Analysis

Build a CNN system for detecting pneumonia in chest X-rays with 95%+ accuracy using transfer learning.

TensorFlow • CNN • Transfer Learning

Speech Recognition System

Create an end-to-end speech-to-text application using RNNs and attention mechanisms.

PyTorch • RNN • Attention • Audio Processing

Art Style Transfer

Implement neural style transfer to create artistic renditions of photographs using CNNs.

TensorFlow • CNN • Style Transfer • VGG

Time Series Forecasting

Predict stock prices and weather patterns using LSTM networks with real-world financial data.

PyTorch • LSTM • Time Series • Finance

Generative AI Application

Build a complete GAN-based application for generating realistic faces or creating art, including a web interface for user interaction.

TensorFlow • GAN • Web Development • Deployment

Prerequisites & Requirements

Technical Prerequisites

Python Programming: Intermediate level with experience in NumPy, Pandas, and Matplotlib
Mathematics: Linear algebra, calculus, and basic statistics knowledge
Machine Learning Basics: Understanding of supervised/unsupervised learning concepts
Development Environment: Familiarity with Jupyter notebooks and command line

System Requirements

Hardware: Computer with at least 8GB RAM, modern CPU (GPU recommended but not required)
Internet: Stable broadband connection for live sessions and cloud computing
Software: We provide access to cloud GPU instances for intensive training
Time Commitment: 15-20 hours per week including lectures, assignments, and projects

Advanced Neural Network Training Excellence

Neural networks represent the cornerstone of modern artificial intelligence applications, powering everything from image recognition systems to autonomous vehicles. Our comprehensive training program provides students with deep understanding of both theoretical foundations and practical implementation techniques required for building production-grade neural network systems.

Industry partnerships with leading technology companies ensure our curriculum remains current with rapidly evolving deep learning research and application methodologies. Students gain hands-on experience with the same tools and frameworks used by AI teams at Google, Facebook, and other innovative organizations driving the future of artificial intelligence.

Project-based learning methodology emphasizes real-world applications and problem-solving skills that employers value most when hiring neural network engineers. Our capstone projects challenge students to build complete AI systems from data preprocessing through model deployment, creating portfolio pieces that demonstrate professional-level competency.

Career advancement support includes technical interview preparation, portfolio development guidance, and networking opportunities with industry professionals who can provide mentorship and job referrals. This comprehensive approach to professional development has resulted in exceptional placement rates and career success stories among program graduates.

Ready to Master Neural Networks?

Join hundreds of professionals who have transformed their careers with our comprehensive deep learning program.

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💳 Interest-free payment plans available • 🔄 30-day money-back guarantee • 🎓 Industry-recognized certificate