Hanna Abi Akl
Chief Academic Officer & Professor at Data ScienceTech Institute
Researcher with the INRIA Wimmics team
Data ScienceTech Institute
4 Rue de la Collégiale
75005 Paris, France
Teaching
Classes are taught in English unless stated otherwise
2024 - 2025
Professor at Data ScienceTech Institute
AI Awareness
Learning Processes in Living Organisms, Learning Processes in Computers, Introduction to AI Ethics, Challenges in AI
Relational Model and SQL
Introduction to the relational model, relational algebra operations, normal forms, database system design & SQL queries
Software Engineering - Part 2
Python Object-oriented Programming, Overview of C++
Deep Learning
PyTorch Introduction, GPU Training, Neural Network Applications (Computer Vision, Natural Language Processing, Reinforcement Learning)
Artificial Neural Networks
Shallow & Deep Artificial Neural Networks, Data Representation & Distributed Representations, Backpropagation & Gradient Descent, Training & Optimization, Python Applications (Tensorflow & Keras)
Python Machine Learning Labs
Data Structures, Cleaning & Preparation, Python Libraries (Numpy, Pandas, Matplotlib, Scikit-learn), Feature Engineering, Machine Learning Algorithms (Linear Regression, Logistic Regression, Decision Trees, Random Forest, KNN, Multi-Layer Perceptron), Classification & Regression
Data Wrangling with SQL
Review of Relational Models & Database Management Systems, Advanced SQL Queries, Dynamic SQL, Stored Procedures & Triggers
Data Management
Fundamentals of information systems analysis & design, Functional dependency, Relation model & relational algebra
Operating Systems and Networking
Fundamentals of algorithmics and data structure design, Fundamentals of network layers, Routing networks layers & protocols, Address spaces and associated service with the TCP/IP suite
Clean IT
Introduction to Google Colab, Python Local Setup, Virtual Environments, IDE Configuration, Jupyter Notebooks, R & RStudio Local Setup, Git & GitHub
2023 - 2024
Professor at Data ScienceTech Institute
Relational Model and SQL
Introduction to the relational model, relational algebra operations, normal forms, database system design & SQL queries
Clean IT
Introduction to Google Colab, Python Local Setup, Virtual Environments, IDE Configuration, Jupyter Notebooks, R & RStudio Local Setup, Git & GitHub
AI Awareness
Learning Processes in Living Organisms, Learning Processes in Computers, Introduction to AI Ethics, Challenges in AI
Data Wrangling with SQL
Review of Relational Models & Database Management Systems, Advanced SQL Queries, Dynamic SQL, Stored Procedures & Triggers
Software Engineering - Part 2
Python Object-oriented Programming, Overview of C++
Amazon AWS
Introduction to Cloud Computing, Cloud Architecture, Preparation for the AWS Certified Solutions Architect – Associate Certification
Python Machine Learning Labs
Data Structures, Cleaning & Preparation, Python Libraries (Numpy, Pandas, Matplotlib, Scikit-learn), Feature Engineering, Machine Learning Algorithms (Linear Regression, Logistic Regression, Decision Trees, Random Forest, KNN, Multi-Layer Perceptron), Classification & Regression
Artificial Neural Networks
Shallow & Deep Artificial Neural Networks, Data Representation & Distributed Representations, Backpropagation & Gradient Descent, Training & Optimization, Python Applications (Tensorflow & Keras)
Deep Learning
PyTorch Introduction, GPU Training, Neural Network Applications (Computer Vision, Natural Language Processing, Reinforcement Learning)
2022 - 2023
Professor at Data ScienceTech Institute
Clean IT
Introduction to Google Colab, Python Local Setup, Virtual Environments, IDE Configuration, Jupyter Notebooks, R & RStudio Local Setup, Git & GitHub
Software Engineering - Part 2
Python Object-oriented Programming, Overview of C++
Python Machine Learning Labs
Data Structures, Cleaning & Preparation, Python Libraries (Numpy, Pandas, Matplotlib, Scikit-learn), Feature Engineering, Machine Learning Algorithms (Linear Regression, Logistic Regression, Decision Trees, Random Forest, KNN, Multi-Layer Perceptron), Classification & Regression
2021 - 2022
Professor at Data ScienceTech Institute
Clean IT
Introduction to Google Colab, Python Local Setup, Virtual Environments, IDE Configuration, Jupyter Notebooks, R & RStudio Local Setup, Git & GitHub
Introduction to Data Structures & Software Engineering
Introduction to Data Structures, Benchmarks in Python & R, Introduction to Data Simulation
Software Engineering - Part 2
Python Object-oriented Programming, Overview of C++
Python Machine Learning Labs
Data Structures, Cleaning & Preparation, Python Libraries (Numpy, Pandas, Matplotlib, Scikit-learn), Feature Engineering, Machine Learning Algorithms (Linear Regression, Logistic Regression, Decision Trees, Random Forest, KNN, Multi-Layer Perceptron), Classification & Regression