website: metadata: name: "Google Reichman AI Tech School" title: "Data Analyst Syllabus - Google Reichman AI Tech School" url: "https://graitechschool.co.il/data-analyst-syllabus" core_info: content_notice: "*Changes may apply" header: primary_elements: - "Data Analyst Syllabus" - "Google Reichman AI Tech School" navigation: [] actions: [] content: - section: title: "Course Overview" description: "Data Analyst Syllabus" elements: - type: "notice" text: "*Changes may apply" - type: "image" alt: "Image 1" url: "https://www.graitechschool.co.il/wp-content/uploads/2022/12/Mask-Group-9042.png" - type: "image" alt: "Image 2" url: "https://www.graitechschool.co.il/wp-content/uploads/2022/12/Gilad-Kavalerchik__221220_130.jpg" actions: [] - section: title: "Module 1: Introduction to Statistics with AI" description: "Pre-course requirement: Consumption of the mandatory podcast/blog reading list on AI fundamentals." elements: - "Introduction to Statistics & AI Agentic Prep in Sheets (Setup of Gemini/Co-pilot assistants; learning to audit data rather than write manual formulas)" - "Introduction to Probability" - "Central & Dispersion Measures: The Logic of Loss" - "Percentiles and Z-Scores: Feature Scaling for ML" - "Common Distributions & Monte Carlo Simulations with Gemini" - "Sampling Distribution & Hypothesis Testing: AI Benchmarking" - "Synthetic Data Generation & Interview Question Simulations (Using AI to generate synthetic datasets to practice technical problem-solving and interview logic)" - "One-Sample Test & Model Bias: Evaluating & Benchmarking AI Outputs (Statistical approaches to LLM Evals, measuring Text-to-SQL accuracy, hallucination rates, and semantic drift via sampling)" - "Confidence Intervals & Two-Samples Tests: Model Reliability" - "Correlations & ML Feature Selection" - "Linear Regression: The Neural Network Ancestor" - "Causal Inference: Measuring Real Lift" - "A/B Testing: 0 to 100 with AI Optimization" actions: [] media: - type: "image" alt: "Image 3" url: "https://www.graitechschool.co.il/wp-content/uploads/2022/12/Gilad-Kavalerchik__221220_146-e1671960198187.jpg" - section: title: "Module 2: Exploratory Data Analysis using SQL, BigQuery & Vibe Coding" elements: - "Database Architecture & Cloud Infrastructure (Self-directed research with AI co-pilot; findings shared in class)" - "SQL Fundamentals, GCP Console, & Basic Querying (Pre-read required: SQL functions with Gemini)" - "Distinct,Where, Logical Operators, & Data Types" - "Advanced Functions & Multimodality (Analyzing unstructured images, text, and video data inside BigQuery)" - "Group By, Having, & Joins" - "Building Your SQL Co-pilot (Setting up AI code assistants and prompt patterns for query generation)" - "Data Modeling for LLMs & Semantic Layers (Understanding how table structure, column naming, metadata, business definitions, and relationships affect AI-generated SQL and analysis)" - "Union, Table Wildcards, & Exporting BQ Results" - "EDA via Vibe Coding (Automated EDA, query generation, and automated ERD creation) –" - "Subqueries & CASE Statements" - "Window Functions" - "Arrays, Structs, & Query Performance Optimization with AI" - "Unstructured Data Cleaning & Synthetic Case Generation" - "SQL Execution Flowcharts & AI Troubleshooting" - "Common Pitfalls & Case Studies" - "Vibe Coding for Data Visualization (Using AI to generate visualizations from BigQuery results and iterating based on analytical insights)" - "EDA Final Project Workshop (Integrating Gemini workflow tools; 1 hour dedicated to AI co-pilot integration)" - "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" actions: [] media: - type: "image" alt: "Image 4" url: "https://www.graitechschool.co.il/wp-content/uploads/2022/12/%D7%A0%D7%99%D7%A1%D7%90-%D7%95%D7%A8%D7%95%D7%A2%D7%99-scaled.jpg" - section: title: "Module 3: Python Workshop & Automation" elements: - "Introduction to Python & AI-Assisted Scripting" - "Exploratory Data Analysis with Python & Pandas" - "Automated A/B Testing Pipelines" - "Agentic Architecture & Function Calling (Using Gemini API and Python function calling to build autonomous, multi-step execution workflows" - "Building AI-Powered Conversation Analysis with Gemini & Python (Processing unstructured text and audio logs)" actions: [] media: - type: "image" alt: "Image 5" url: "https://www.graitechschool.co.il/wp-content/uploads/2022/12/Gilad-Kavalerchik__221220_146-e1671960198187.jpg" - section: title: "Module 4: Modern Data Visualization & GenAI BI" elements: - "Real Use Cases of BI in Product Organizations" - "How Generative AI is Transforming BI & Visual Storytelling" - "Conversation-Driven Dashboards: GenAI Chat inside BI platforms & Talking to Dashboards via Gemini Live" - "Advanced BI Integrations: MCPs (Data Studio + MCP Toolbox) &NotebookLM for Strategy Brainstorming" actions: [] media: - type: "image" alt: "Image 6" url: "https://www.graitechschool.co.il/wp-content/uploads/2022/12/%D7%90%D7%A0%D7%92%D7%9C%D7%99-scaled.jpg" - section: title: "Module 5: Product Analysis & Unstructured Data Apps" elements: - "Programmatic Advertising & Metric Selection" - "Traditional & AI-Native Product Analytics AI Studio for Analytics: Building Rapid, Robust Unstructured Data Analysis Apps for calculating Retention, Churn, Funnels and more" - "Scoping UX Research, Business KPIs, & “Aha!” Moments" - "Final Capstone Project Guidance & AI Workflow Review" actions: [] media: - type: "image" alt: "Image 7" url: "https://www.graitechschool.co.il/wp-content/uploads/2022/12/%D7%92%D7%9C-%D7%95%D7%90%D7%93%D7%99%D7%A1%D7%9C%D7%90%D7%9D-scaled.jpg" - section: title: "Module 6: Power Skills, Industry Mentorship & Personal Branding" elements: - "Personal Branding & Content Creation: Immediate post-statistics workshop on creating technical content and sharing learnings on LinkedIn" - "Industry Mentorship: Direct matching with our network of active industry mentors for career guidance, resume reviews, and portfolio feedback" - "AI-Powered Interview Practice: Prompting frameworks to reverse-engineer interview questions for specific companies and target roles" - "Professional Execution: Public speaking, storytelling with data, stakeholder negotiation, and driving business decisions with VPs of Product and Finance" actions: [] - section: title: "Final Notice" elements: - "*Changes may apply" actions: [] footer: links: [] info: [] social: []