Learning Goals

AIcademy Summer Camp offers a 10-day course with the following learning goals

Module 1

Introduction to Artificial Intelligence and Machine Learning

  • Grasp the foundational concepts
  • Applications of AI
  • Limitations of AI

Basics of Python Programming and Common Data Science Frameworks

  • Learn the basics of Python programming language
  • Understand Python applications in data science
  • Gain familiarity with essential libraries and algorithms tailored specifically for data science applications

Module 2

Basic Supervised Machine Learning and Algorithms

  • Gain a comprehensive understanding of the theoretical underpinnings of machine learning and put them into practical application

Supervised Machine Learning

  • Learn the foundational concepts of classification
  • Gain skills to optimize model parameters by minimizing an objective (loss) function

Model Building and Validation

  • Learn how to construct and validate a machine-learning model
  • Curate a repository of models, encompassing various classification algorithms available in the scikit-learn library

Unsupervised Machine Learning and Clustering

  • Discover the powerful technique of clustering
  • Gain a comprehensive understanding of key clustering algorithms, including DBSCAN
  • Learn how to leverage clustering algorithms to unveil latent patterns within datasets

Module 3

Mastering Dimensionality Reduction and Principle Component Analysis (PCA):

  • Grasp the essence of dimensionality reduction, specifically focusing on elucidating linear relationships among dataset features

Exploring Text Mining Techniques

  • Learn fundamental text mining concepts, including the construction of embeddings from phrases and the interpretation of terms such as Term Frequency (TF) and Inverse Document Frequency (IDF)
  • Construct a classifier capable of performing basic sentiment analysis on provided texts

Module 4

Neural Networks

  • Gain a comprehensive understanding of Neural Networks, encompassing both theoretical concepts and practical applications
  • Explore the concept of convolution and its pivotal role in convolutional neural networks (CNNs)
  • Understand advanced image processing techniques

Module 5

Introduction to the Transformer Architecture

  • Gain a thorough understanding of the fundamental principles underlying the transformer architecture
  • Proficiently describe essential components such as position encoding and the attention mechanism

Building a Chatbot

  • Engage in constructing a simple yet functional chatbot
  • Acquire the expertise to fine-tune a Large Language Model (LLM)
  • Enhance the understanding of practical applications of transformer architectures in real-world scenarios

Module 6

AI Ethics

  • Explore the ethical dimensions of Artificial Intelligence (AI)
  • Gain an understanding of the profound societal implications of AI technologies
  • Recognize that developed AI models have the potential to impact diverse communities

Module 7

Generative AI

  • Gain a comprehensive understanding of various AI tools for multiple utilizations
  • Understand the functionalities and applications of diverse AI tools
  • Acquire practical experience through guided exercises and demonstrations

Module 8

Teamwork and Project Management

  • Immerse in challenging projects akin to those encountered in a Hackathon
  • Cultivate essential teamwork and project management skills