*Changes may apply

Syllabus Data Analyst

In the Google and Reichman Data Analyst program, we live by a simple rule: without data, you’re just another person with an opinion; but without an opinion, you’re just another person with data. In a world where AI can generate charts in seconds, the technical/coding "how-to" is no longer enough. The real value now lies in your judgment and your ability to think critically about what the numbers actually mean. We’ve designed this program to give you that edge, integrating AI into every step—from writing code and mastering statistics to nailing your technical interviews. What does this actually mean for your day-to-day career? Once you land a role in a top tech organization, your day won't be spent stuck in manual data entry or basic spreadsheet cleanup. Instead, you’ll be the person driving the strategy. You’ll learn directly from instructors who lead teams at top companies, showing you exactly how they integrate AI tools into their real-world workflows. Beyond the basics, you'll master SQL for big data, cloud-based visualization, and Python automation to handle scale. • Handling the "Messy" Stuff: You’ll use Gemini and Python to build conversation analysis tools and AI Studio to pull insights from unstructured data that others can't even process. • Bulletproof Logic: You’ll use synthetic AI data to stress-test your stats, ensuring that when you make a recommendation to a VP of Product or Finance, your logic is unshakeable. • The Power of Persuasion: You’ll use "vibe coding" to quickly turn exploratory data into a narrative that doesn't just show numbers, but convinces stakeholders to take action. You’ll walk away with the ability to provide strategic guidance to Engineering, Product, and Finance teams. We aren't just teaching you how to use tools; we’re training you to be the expert who uses AI to work faster, think deeper, and lead the conversation.

Introduction to statistics

 

  • Intro to the AI Era
  • Introduction to Statistics
  • Introduction to probability & LLM Token Logic
  • Central and Dispersion Measures: The Logic of Loss
  • Introduction to Google Sheets & AI Agentic Prep
  • Percentiles and Z-Scores: Feature Scaling for ML
  • Common Distributions & Monte Carlo Simulations with Gemini
  • Sampling Distribution and Hypothesis Testing: AI Benchmarking
  • One-Sample Test: Testing for Model Bias
  • Confidence Intervals and Two-Samples Tests: Model Reliability
  • Correlations & ML Feature Selection
  • Linear Regression: The Neural Network Ancestor
  • Causal Inference: Measuring A Real Lift
  • A/B Test: 0 to 100 with AI Optimization

Introduction to exploratory data analysis using SQL and Big Query

 

  • Introduction to Big Data and & Databases
  • SQL introduction, GCP Console, Select, From, Limit, Aliases
  • Distinct, Where, Logical operators, Data Types
  • Functions
  • Group by, Having, Join
  • Union, Table wildcard, Exporting BQ results & Plotting in Google Sheets
  • EDA Example (explore a dataset using SQL + build ERD)
  • Subqueries, CASE
  • Window Functions
  • Arrays, Structs, Query Performance
  • Data Cleaning
  • SQL Flowchart
  • Common Pitfalls and Case Studies Practice
  • My first AI Agent
  • Data Visualization and EDA Fundamentals (Vibe code your visualization)
  • EDA Project A-Z
Python Workshop

 

  • Intro to Python and Data
  • Data Exploration with Python
  • A/B Testing
  • Building AI-Powered Conversation Analysis with Gemini and Python

 

 

Data Visualization

 

  • Real use cases of BI in organizations
  • How Generative AI is transforming BI and visual storytelling?
  • GenAI powered chat inside the BI
  • MCPs – Data Studio + MCP Toolbox
  • Talk with your dashboards with Gemini Live
  • NotebookLM : an amazing tool for brainstorming and data visualization
Product Analysis

 

  • Intro to programming advertising
  • Pick the right metric
  • Product analysis – Retention and Churn, Funnel Analysis
  • Using AI Studio for building quick and robust analysis apps
  • Scoping UX Research, KPI and aha Moments
  • Final Project
Power Skills

The “Power Skills” section is all about building the practical abilities you need to succeed in your career. This chapter is packed with hands-on exercises and practical tips to help you develop and improve skills like public speaking, time and task management, teamwork, decision making, interviewing, creating a personal LinkedIn profile and resume. This comprehensive skill development module aims to equip you with the essential tools for a successful career path.

*Changes may apply