Artificial Intelligence & Machine Learning
This 16-hour foundation program introduces the core concepts of Artificial Intelligence and Machine Learning, including supervised and unsupervised learning, algorithms, model evaluation, and real-world applications.
Syllabus
- Introduction to AI and ML
- Data Preprocessing & Feature Engineering
- Supervised Learning – Regression & Classification
- Unsupervised Learning – Clustering
- Model Evaluation & Metrics
- Real-world ML Project
Business Analytics
This 16-hour program equips learners with essential analytical thinking skills, business intelligence tools, and data-driven decision-making competencies.
Syllabus
- Introduction to Business Analytics
- Descriptive, Predictive & Prescriptive Analytics
- KPIs, Dashboards & Data Visualization
- Analytics for Marketing, Finance & Operations
- Case Studies & Business Insights
Power BI – 12 Weeks
A complete 12-week practical program covering modern BI dashboards, DAX functions, Power Query, data modelling and automation pipelines.
Syllabus
- Introduction to BI & Power BI Desktop
- Power Query & Data Transformation
- Data Modelling & DAX Fundamentals
- Advanced DAX & Calculated Tables
- Interactive Dashboards & Visuals
- Publishing, Automation & Power BI Service
Python for Data Science – 12 Weeks
A complete hands-on program covering Python basics, data structures, NumPy, Pandas, Matplotlib, Seaborn, and introductory machine learning.
Syllabus
- Python Basics & Data Structures
- NumPy Foundations
- Pandas for Data Analysis
- Data Cleaning & Exploration
- Visualization with Matplotlib & Seaborn
- Introductory Machine Learning with Scikit-Learn
Introduction to Machine Learning – 12 Weeks
A structured introduction to ML theory and practice, including essential algorithms, model building, evaluation, and tuning.
Syllabus
- What is Machine Learning?
- Data Preprocessing & Feature Selection
- Regression & Classification Algorithms
- Clustering Techniques
- Model Evaluation Techniques
- Mini Project
R Programming – 8 Weeks
An essential course on R for data analysis, visualization, statistical modelling, and reporting.
Syllabus
- R Basics & RStudio
- Data Structures in R
- dplyr for Data Manipulation
- Visualization with ggplot2
- Statistics & Modelling in R
- Capstone Mini Project