Data Science and Artificial Intelligence

Objective of the Training

This course aims to train participants in Data Science and Artificial Intelligence, equipping them with the skills to analyze data, build predictive models, automate processes, and make data-driven decisions in real-world scenarios.

Target Audience

• Developers and IT professionals looking to specialize in data and AI
• Students in computer science, mathematics, or engineering
• Professionals seeking career transition into data analysis, machine learning, or AI

Prerequisites

• Basic programming knowledge (Python preferred)
• Basic knowledge of statistics and mathematics
• Familiarity with data concepts is an advantage but not required

Modalities

• Language: English or French depending on student preference
• Format: Online or in-person
• Schedule: Daytime or evening according to your availability
• Duration: 3 to 6 months (depending on chosen pace)
• Methodology: 100% practical, with hands-on exercises and real datasets
• Provided Materials: Access to datasets, cloud computing resources, and AI/ML tools

Detailed Program

Module 1: Introduction to Data Science & AI

• Overview of Data Science, Machine Learning, and AI
• Applications in business, industry, and research
• Tools and programming environments (Python, Jupyter Notebook)

Module 2: Data Analysis & Visualization

• Data collection and cleaning
• Exploratory Data Analysis (EDA)
• Visualization with Matplotlib, Seaborn, and Plotly

Module 3: Statistics & Probability for Data Science

• Descriptive and inferential statistics
• Probability distributions
• Hypothesis testing

Module 4: Machine Learning Fundamentals

• Supervised and unsupervised learning
• Regression, classification, and clustering algorithms
• Model evaluation and validation

Module 5: Advanced Machine Learning & AI Techniques

• Neural networks and deep learning basics
• Natural Language Processing (NLP)
• Computer vision and image recognition

Module 6: Big Data & Cloud Integration

• Introduction to Big Data technologies (Hadoop, Spark)
• Data storage and processing in the cloud
• Integration with AI workflows

Module 7: Final Project / Capstone

• Build a real-world AI model or data application
• Present results with dashboards and reports
• Demonstrate practical data-driven decision-making

Certifications and Skills Acquired

• Data analysis and visualization with Python
• Machine learning model building and evaluation
• AI model deployment in cloud environments
• Preparation for certifications in Data Science and AI