AI & Data Science
Deep Learning & Neural Networks
A focused deep-dive into neural networks: from perceptrons to CNNs, RNNs, autoencoders and generative models. Strongly project-oriented, ending in a deployment-ready capstone and portfolio.
Skills you'll gain
Deep learningANN / CNN / RNNAutoencodersComputer visionNLPGenerative AIModel training & optimisation
Curriculum
11 modules · tap any module to expand.
Deep Learning Foundations
Introduction to deep learningEvolution of AIApplications across industries
Artificial Neural Networks (ANN)
Neurons, layers & activationsForward & back-propagationTraining deep models
Computer Vision with CNNs
Convolutional neural networksFeature maps & poolingImage classification projects
Sequential Data & RNNs
Recurrent neural networksSequence modellingTime-series & text processing
Self-Organizing Maps
SOM fundamentalsClustering & visualisationPractical SOM projects
Energy-Based Models
Boltzmann machinesRestricted Boltzmann machinesDeep belief networks
Autoencoders
Encoder–decoder architectureDimensionality reductionAnomaly detectionImage compression
NLP & Sentiment Analysis
Text preprocessingSentiment modelsReal-world NLP
Generative AI & Text Creation
Language modellingSequence generationCreative AI
Advanced & Modern AI
Advanced architecturesTransfer learningFoundation models
Capstone & Future of AI
End-to-end deep-learning solutionDeployment preparationIndustry trends & career guidance
Career paths
- Deep Learning Engineer
- AI Engineer
- Computer Vision Engineer
- NLP Engineer
- Generative AI Engineer
Projects you'll build
- CNN image-classification system
- Sentiment-analysis engine
- Autoencoder image compression
- Advanced deep-learning capstone
Not sure if this is the right fit?
Book a free counselling call and we'll map Deep Learning & Neural Networks to your background and goals.