AI+ Data™
Mastering AI, Maximizing Data: Your Path to Innovation
This course covers core concepts including Data Science foundations, Python, Statistics, and Data Wrangling, building a strong analytical base. It progresses into advanced topics such as Generative AI, Machine Learning, and Predictive Analytics, equipping learners with modern AI-driven capabilities. Through a capstone application, participants solve real-world challenges like employee attrition using AI techniques. With a focus on career readiness, the course develops practical skills for AI-powered data science roles, supported by hands-on mentorship.
Enrollment Fee:
MUR 15,145
What You'll Learn
- Course Introduction
1.1 Introduction to Data Science
1.2 Data Science Life Cycle
1.3 Applications of Data Science
2.1 Basic Concepts of Statistics
2.2 Probability Theory
2.3 Statistical Inference
3.1 Types of Data
3.2 Data Sources
3.3 Data Storage Technologies
4.1 Introduction to Python for Data Science
4.2 Introduction to R for Data Science
5.1 Data Imputation Techniques
5.2 Handling Outliers and Data Transformation
6.1 Introduction to EDA
6.2 Data Visualization
7.1 Introduction to Generative AI Tools
7.2 Applications of Generative AI
8.1 Introduction to Supervised Learning Algorithms
8.2 Introduction to Unsupervised Learning
8.3 Different Algorithms for Clustering
8.4 Association Rule Learning with Implementation
9.1 Ensemble Learning Techniques
9.2 Dimensionality Reduction
9.3 Advanced Optimization Techniques
10.1 Introduction to Data-Driven Decision Making
10.2 Open Source Tools for Data-Driven Decision Making
10.3 Deriving Data-Driven Insights from Sales Dataset
11.1 Understanding the Power of Data Storytelling
11.2 Identifying Use Cases and Business Relevance
11.3 Crafting Compelling Narratives
11.4 Visualizing Data for Impact
12.1 Project Introduction and Problem Statement
12.2 Data Collection and Preparation
12.3 Data Analysis and Modeling
12.4 Data Storytelling and Presentation
1. Understanding AI Agents
2. Case Studies
3. Hands-On Practice with AI Agents
Prerequisites
- Basic knowledge of computer science and statistics (beneficial but not mandatory).
- Keen interest in data analysis.
- Willingness to learn programming languages such as Python and R.
Exam Details
Duration:
90 minutes
Passing Score:
70% (35/50)
Format:
50 multiple-choice/multiple-response questions
Delivery Method:
Online via proctored exam platform (flexible scheduling)
Unlock Self-Paced Online Learning
- Unlock Self-Paced Online Learning
- Access learning anytime, anywhere, with built-in quizzes to measure progress.
- Enrollment Fee: MUR 15,145