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Become a certfied
Data Analyst

Unlock the power of data. Learn how to collect, analyze, and interpret data to drive smarter decisions in tech, business, and beyond.

  • Admission status

    Stopped

  • Tuition status

    Ongoing

  • Venue

    Online (Live)

  • Programme starts

    To be announced

frontend developement

Course Outline

  • Module 1
    • Duration
    • Weeks 1–2

    Foundations

    Understand what data analytics is and learn basic tools and concepts.

    • Topics

    • Introduction to Data Analytics

      Learn what data analytics is, its importance in decision-making, and its role in business and technology.

    • Types of Data Analytics

      Understand the four main types: Descriptive, Diagnostic, Predictive, and Prescriptive analytics.

    • Microsoft Excel or Google Sheets

      Learn basic spreadsheet operations, formulas, functions, charts, and pivot tables.

    • Projects

    • Sales Dashboard in Excel

    • Data Cleaning and Summary Report

  • Module 2
    • Duration
    • Weeks 3–4

    Data Handling with SQL

    Learn to query, filter, and manipulate data using SQL.

    • Topics

    • SQL Basics

      Understand SELECT, FROM, WHERE, ORDER BY, and LIMIT statements for querying data.

    • Aggregations and Grouping

      Use GROUP BY, COUNT, SUM, AVG, and HAVING to summarize data.

    • Joins and Subqueries

      Learn how to combine data from multiple tables using INNER, LEFT, RIGHT, and FULL JOINs.

    • Data Filtering and Cleaning

      Use SQL functions to filter nulls, duplicates, and incorrect entries.

    • Projects

    • Customer Sales Analysis with SQL

    • Employee Database Report

  • Module 3
    • Duration
    • Weeks 5–6

    Statistics for Data Analysis

    Develop statistical thinking for analyzing and interpreting data.

    • Topics

    • Descriptive Statistics

      Learn mean, median, mode, standard deviation, variance, and percentiles.

    • Data Distributions

      Understand normal distribution, skewness, and outliers.

    • Probability and Sampling

      Explore basic probability, sampling techniques, and sample size considerations.

    • Hypothesis Testing

      Learn to perform t-tests, chi-square tests, and interpret p-values and confidence intervals.

    • Projects

    • Customer Retention Hypothesis Test

    • Sales Distribution Analysis

  • Module 4
    • Duration
    • Weeks 7–8

    Data Visualization

    Effectively visualize and communicate data insights.

    • Topics

    • Data Visualization Principles

      Learn how to choose the right chart type and present data clearly and effectively.

    • Using Tableau or Power BI

      Create interactive dashboards using drag-and-drop visualization tools.

    • Visualization with Excel

      Create line charts, bar charts, scatter plots, and pivot charts.

    • Storytelling with Data

      Learn how to present insights using narratives and visuals to influence decision-making.

    • Projects

    • Sales Dashboard in Power BI or Tableau

    • KPI Dashboard for a Marketing Campaign

  • Module 5
    • Duration
    • Weeks 9–11

    Data Analysis with Python

    Use Python for powerful, flexible data analysis.

    • Topics

    • Python Basics for Analytics

      Learn variables, data types, loops, conditionals, and functions relevant for analysis.

    • Pandas Library

      Use Pandas for dataframes, data cleaning, grouping, filtering, and aggregations.

    • NumPy and Math Operations

      Use NumPy for numerical operations and array handling.

    • Data Visualization in Python

      Use Matplotlib and Seaborn to create charts, heatmaps, and plots for analysis.

    • Projects

    • Retail Sales Data Cleaning and EDA

    • Exploratory Analysis of Survey Data

  • Module 6
    • Duration
    • Weeks 12–14

    Advanced Analytics and Tools

    Explore advanced topics and tools to gain deeper insights.

    • Topics

    • Time Series Analysis

      Analyze trends over time using line graphs, rolling averages, and seasonality detection.

    • A/B Testing

      Design and analyze experiments to test performance differences between two or more options.

    • Web Analytics

      Use tools like Google Analytics to understand user behavior, traffic sources, and conversion metrics.

    • Data Ethics and Privacy

      Understand ethical use of data, privacy laws (e.g., GDPR), and data anonymization.

    • Projects

    • Website Traffic & Conversion Funnel Analysis

    • Time-Based Sales Trend Report

  • Module 7
    • Duration
    • Weeks 15–16

    Capstone Projects and Portfolio

    Build your portfolio and prepare for job applications.

    • Topics

    • Capstone Project Planning

      Choose a real-world dataset and define questions and methods for your analysis.

    • Data Cleaning and EDA

      Prepare data and conduct exploratory analysis using learned tools (SQL, Excel, Python).

    • Insight Generation and Presentation

      Create visual dashboards or reports and present actionable insights.

    • Projects

    • Capstone Project: Business Intelligence Report

    • Capstone Project: Product Usage Analysis

  • Module 8

    Final Step: Job Readiness

    Prepare for a career in data analytics.

    • TASKS

    • Build and host a professional portfolio

    • Upload projects to GitHub or Tableau Public

    • Prepare a resume with quantifiable achievements

    • Practice case study interviews and SQL/Python questions

    • Apply to entry-level data analyst roles or internships

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