TechX — Technology & Software

Data Science & Analytics

Collect, Analyse, Decide

Learn Data Science and Analytics from data collection and processing to machine learning and business intelligence. This programme covers the complete data pipeline — from cleaning raw data to building predictive models and creating dashboards that drive business decisions.

12 Sessions
4 Certifications
Expert Mentors
100% Project-Based

What you'll learn

Master Python and SQL for data analysis
Clean, process, and transform large datasets
Build machine learning models for prediction and classification
Create interactive data visualisations and dashboards
Work with real-world business datasets
Apply statistical analysis and hypothesis testing
Use Power BI and Tableau for business intelligence
Deploy data science projects end to end

Course curriculum

Introduction to Data Science

  • What is Data Science and its Applications
  • Data Science Workflow and Lifecycle
  • Types of Data and Data Sources
  • Introduction to Python for Data Science
  • Setting Up Data Science Environment

Python for Data Analysis

  • Python Fundamentals Review
  • NumPy for Numerical Computing
  • Pandas for Data Manipulation
  • Data Import — CSV, Excel, JSON, SQL
  • Data Exploration and Profiling

Data Cleaning & Preprocessing

  • Handling Missing Values and Outliers
  • Data Type Conversion and Formatting
  • Feature Engineering Techniques
  • Data Normalisation and Standardisation
  • Preparing Data for Machine Learning

Exploratory Data Analysis (EDA)

  • Descriptive Statistics and Distributions
  • Correlation Analysis
  • Data Visualisation with Matplotlib and Seaborn
  • Identifying Trends and Patterns
  • EDA on Real Business Datasets

SQL for Data Analysis

  • SQL Fundamentals — SELECT, WHERE, JOIN
  • Aggregations and GROUP BY
  • Subqueries and Window Functions
  • Connecting SQL Databases to Python
  • Data Analysis Projects with SQL

Statistical Analysis & Hypothesis Testing

  • Probability and Distributions
  • Hypothesis Testing — t-Test, Chi-Square, ANOVA
  • Confidence Intervals and P-Values
  • A/B Testing for Business Decisions
  • Statistical Thinking in Data Science

Machine Learning for Data Science

  • Supervised Learning — Regression and Classification
  • Unsupervised Learning — Clustering
  • Model Training, Evaluation and Selection
  • Cross-Validation and Hyperparameter Tuning
  • Machine Learning Pipeline Development

Data Visualisation & Storytelling

  • Advanced Visualisation with Plotly and Seaborn
  • Dashboard Design Principles
  • Creating Interactive Charts and Graphs
  • Communicating Data Insights to Stakeholders
  • Data Storytelling Best Practices

Business Intelligence — Power BI

  • Introduction to Power BI Desktop
  • Connecting Data Sources to Power BI
  • DAX Formulas and Calculated Columns
  • Building Interactive Dashboards
  • Publishing and Sharing Reports

Tableau for Analytics

  • Introduction to Tableau Desktop
  • Connecting and Preparing Data in Tableau
  • Building Charts, Maps and Dashboards
  • Tableau Calculated Fields and Filters
  • Publishing to Tableau Public

Big Data & Cloud Analytics

  • Introduction to Big Data — Hadoop and Spark
  • Google BigQuery for Large-Scale Analysis
  • AWS Analytics Services Overview
  • Real-Time Data Streaming Basics
  • Cloud-Based Data Pipelines

Capstone Project & Career Preparation

  • End-to-End Data Science Project
  • Portfolio Dashboard Creation
  • Data Analyst Interview Preparation
  • Building a Data Science Resume
  • Career Pathways in Data Science

Certifications you'll earn

Microsoft Azure Data Fundamentals
Certificate of Training
Certificate of Internship
Certificate of Excellence

24/7 Mentor Support + Placement Assistance

Get help from experienced industry mentors whenever you need it. Placement guidance is built into every programme.

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