AI Academy - Full time (40h/week)

The AI Academy is a technical, project-oriented training programme structured around core modules, specialised tracks, and a final capstone project. It provides participants with a structured pathway to develop competencies in Artificial Intelligence through progressive learning and practical application. This programme is delivered full-time (40h/week) and combines theoretical foundations with practical application.

In this academy, you will work on hands-on projects covering the following topics:

Common Core Program (2 months / 40h per week)

• Python Programming
• • Python syntax, data types, and structures
  • Functions, loops, and conditionals
  • File handling and exceptions
  • Object-Oriented Programming
  • Modules and Packages
• Linear Algebra
• • Scalars, Vectors and Matrices
  • Matrix Operations
  • Determinants
  • Eigenvalues and Eigenvectors
• Calculus
• • Limits and Derivatives
  • Chain Rule and Partial Derivatives
  • Integration basics
• Probability
• • Probability Distributions
  • Mean, variance, and standard deviation
  • Bayes’ theorem and conditional probability
• Data Manipulation
• • Pandas workflow
  • Introduction to visualization

After the Common Core, you will have the opportunity to choose one of the following two specializations:

Machine Learning Specialization program (4 months / 40h per week)

• Classical Machine Learning
• • Regression models
  • Classification models
• Deep Learning Fundamentals
• • Neural Network Basics & Architectures
  • Training & Optimization
  • Regularization Techniques
• Advanced Deep Learning
• • Transfer Learning
  • Autoencoders
  • Generative Models
• Natural Language Processing (NLP)
• • Word embeddings
  • Sequence Modeling (RNN, LSTM, GRU)
  • Transformer architecture
• Reinforcement Learning
• • Fundamentals of Reinforcement Learning
  • Value-Based Methods
  • Policy-Based Methods

Data Science specialization Program (3 months / 40h per week)

• Data Handling
• • Data collection
  • Exploratory Data Analysis
  • Data Preprocessing
  • Working with databases
• Supervised Learning
• • Regression and Classification overview
  • Linear Models
  • Tree-Based Models
  • Model evaluation and tuning
  • Pipeline building with Scikit-learn
• Unsupervised Learning
• • Clustering
  • Dimensionality reduction
• Advanced AI
• • Neural Networks
  • Computer Vision
  • Generative AI

The AI Academy follows a project-oriented approach designed to provide hands-on experience while allowing flexibility for participants.

• Project-Based Learning: Participants work on real-world projects throughout the programme, applying theoretical knowledge to practical challenges.
• Flexible Schedule: Participants can work on their projects at their convenience, including evenings and weekends, while still meeting programme milestones.
• Mandatory On-Site Presence: All participants are required to attend on-site sessions on a weekly basis every Monday, which include guided technical instruction, keynote presentations, and soft skills workshops. 
  
• Integrated Skills Development: On-site sessions combine both technical competencies and professional skills, ensuring a well-rounded training experience.