Module 1: Foundations of Data Analytics & Analytical Thinking

Introduces the analytical mindset, data types, data structures, analytical workflows, problem framing, and the role of analytics in modern business decision-making.

Module 2: Data Collection, Cleaning & Preparation Techniques

Covers ETL processes, handling missing values, data profiling, data quality checks, transformation techniques, and preparing datasets for analysis.

Module 3: Statistical Analysis, Probability & Exploratory Data Analytics (EDA)

Explores descriptive and inferential statistics, hypothesis testing, probability concepts, correlation analysis, and EDA techniques using visual and numerical tools.

Module 4: SQL, Databases & Data Querying for Analytics

Teaches database concepts, relational schemas, joins, aggregations, filtering, and writing SQL queries to extract and manipulate data effectively.

Module 5: Python for Data Analytics & Automation

Covers Python fundamentals, data manipulation libraries (Pandas, NumPy), automation scripts, and applying Python to real-world analytical problems.

Module 6: Data Visualisation & Business Intelligence Dashboards

Focuses on visual storytelling, chart selection, dashboard design, KPIs, and using BI tools such as Power BI or Tableau to present insights clearly.

Module 7: Predictive Analytics, Machine Learning Basics & Model Evaluation

Introduces regression, classification, clustering, model training, validation, performance metrics, and interpreting outputs to support decision-making.

Module 8: Applied Analytics, Case Studies & Real-World Projects

Provides hands-on applications in marketing analytics, finance analytics, operations optimisation, customer segmentation, and end-to-end analytics project execution.

• Core concepts of modern data analytics

• Data cleaning, preparation, and transformation techniques

• Statistical analysis, EDA, and insight generation

• SQL querying and database interaction

• Python programming for analysis and automation

• Designing intuitive dashboards and BI reports

• Basics of machine learning and predictive modelling

• Applying analytics to real-world business challenges

• Data analysts and aspiring data professionals

• Business analysts, researchers, and strategists

• Finance, marketing, and operations professionals

• IT officers transitioning into data roles

• Students pursuing tech or analytics careers

• Anyone seeking to develop strong data-driven decision skills