Foundation Analyst Program

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About Course

The Foundation Analyst Program is a 3–4 month beginner-friendly course designed to build strong analytical thinking and technical skills required to start a career in data and business analytics.

This program provides a step-by-step introduction to data analytics, covering everything from the fundamentals of analytics, Excel proficiency, data visualization, basic statistics, databases, and introductory cloud concepts.

Students will learn through hands-on exercises, real-world datasets, and guided projects — ensuring not just theoretical understanding but also practical readiness for entry-level analyst roles.

The program also includes a dedicated Job Readiness component, helping learners craft resumes, prepare for interviews, build personal web portfolios, and understand real industry workflows.

By the end of this program, learners will be ready to pursue opportunities such as Data Analyst Intern, Business Analyst Trainee, or Reporting Executive.

 

⏱️ Total Course Duration

  • Duration: 3 to 4 Months

  • Total Learning Hours: Approx. 120–150 Hours

    • Instructor-led Sessions: 50+ hours

    • Practical Exercises and Projects: 60+ hours

    • Assignments, Quizzes & Portfolio Work: 30+ hours

  • Flexible: Learn at your own pace with live mentorship and recorded sessions.

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What Will You Learn?

  • Understand the fundamentals of data analytics and its role in business decision-making.
  • Gain hands-on experience in Excel for data cleaning, transformation, and analysis.
  • Learn data visualization principles and create professional dashboards.
  • Apply basic statistics and descriptive analytics to summarize and interpret data.
  • Understand database concepts and SQL for querying and managing data.
  • Learn to solve real-world business problems using analytical frameworks.
  • Get introduced to cloud computing concepts and cloud-based data ecosystems.
  • Develop job readiness skills – from resume building to interview preparation and personal branding.

Course Content

Introduction to Analytics & Data Ecosystem
This module introduces learners to the fundamental concepts of analytics, the data ecosystem, and how data is transformed into actionable insights for businesses. Students will explore different types of analytics, data sources, key roles in the analytics domain, and the modern data workflow from raw data to decision-making.

  • What is Analytics and Why It Matters
  • The Data Analytics Lifecycle
  • Key Roles in the Analytics Domain
  • Types of Analytics
  • The Modern Data Ecosystem
  • Industry Case Studies
  • Data Sources and Data Types0
  • Analytics Fundamentals
  • Identify Analytics in Action
  • Map the Analytics Lifecycle
  • Roles in Analytics

Framing the Right Questions
Before analyzing data, it’s critical to ask the right questions. This section teaches you how to translate vague business problems into clear, measurable analytical questions, select the right KPIs, and build hypotheses that guide your analysis. By the end of this section, you’ll know how to frame problems so data can drive actionable insights.

Understanding Data Basics
Data is the backbone of all analysis. In this section, you’ll learn the different types of data, where it comes from, and why data quality matters. Understanding data basics ensures you can clean, prepare, and analyze datasets effectively, forming the foundation for all analytical work.

Excel for Analysts
Excel is one of the most widely used tools for data analysis. In this section, you’ll learn how to use formulas, clean and transform data, create pivot tables, build dashboards, and automate repetitive tasks. By the end, you’ll be able to analyze datasets efficiently and present insights in a clear, visual format.

SQL Fundamentals
SQL is the language of databases and a core skill for analysts. In this section, you’ll learn how to retrieve, filter, aggregate, and combine data from tables. By the end, you’ll be able to query databases confidently and perform basic data analysis using SQL.

Data Cleaning & Preparation
Before any meaningful analysis, data must be clean, consistent, and structured. This section covers essential data cleaning techniques, combining multiple data sources, and preparing datasets for analysis. By the end, you’ll be able to handle messy data and create analysis-ready datasets.

Introductory Statistics
Statistics is the backbone of data analysis. This section introduces fundamental statistical concepts like measures of central tendency, variability, distributions, and the difference between correlation and causation. By the end, you’ll be able to summarize datasets and interpret basic statistical results for informed decision-making.

Data Visualization & Storytelling
Data is most impactful when it tells a story. This section teaches how to visualize data effectively, design dashboards, and craft narratives that communicate insights clearly. By the end, you’ll be able to transform raw numbers into compelling, actionable stories for stakeholders.

Communicating Insights
Analyzing data is only valuable if insights are communicated effectively. This section teaches how to write concise executive summaries, present findings to non-technical audiences, and structure recommendations for maximum impact. By the end, you’ll be able to convey insights clearly and drive action.

Tools, Workflow & Collaboration
Being an effective analyst isn’t just about analyzing data—it’s also about working efficiently and collaboratively. This section covers file versioning, documenting datasets, automating repetitive tasks, scheduling reports, and best practices for collaborating with teams. By the end, you’ll understand how to manage workflows and communicate clearly in a professional environment.

Ethics, Privacy & Data Governance
Data analysts must handle information responsibly. This section introduces key concepts in data ethics, privacy, bias, and governance. By the end, you’ll understand how to protect sensitive data, avoid biased analysis, and comply with legal and organizational standards.

Capstone Project – End-to-End Analysis
The capstone project is your opportunity to bring together everything you’ve learned in the Foundation Program. You will complete an end-to-end analysis, from understanding a business problem to communicating actionable insights. This hands-on experience simulates real-world analyst work and demonstrates your ability to handle a complete data workflow.

Job Readiness Components

Certification Criteria: Foundation Program — Analyst
To earn the “Certified Foundation Analyst” badge, learners must successfully complete the following:Complete All Lessons and QuizzesFinish every lesson from Sections 1–12Attempt and pass all 11 quizzesSubmit All Practical AssignmentsComplete exercises, activities, and assignments from each sectionInclude Excel dashboards, SQL queries, data cleaning tasks, and one-page summariesComplete the Capstone ProjectDeliver an end-to-end analysis including problem statement, cleaned dataset, analysis, dashboard, and one-page insight summary

Earn a certificate

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