Your Four-Month Practical Learning Journey
Develop practical Data Analyst skills through a structured pathway covering SQL, Python, data preparation, business dashboards, responsible AI-assisted analytics and an integrated capstone project.
Learn the Complete Data Analyst Workflow
This program takes you from understanding a business question to retrieving, preparing, analyzing and visualizing data. You will also learn how to communicate findings and use AI responsibly to support analytical work.
Each month develops a different part of the workflow. Lessons are introduced in a practical sequence so that every new skill builds upon the work completed earlier.
What You Will Learn and Produce
The program follows the order in which analysts commonly work with business data: retrieve it, prepare it, visualize it and use the complete process to solve a business problem.
SQL for Data Analysis
Learn how to retrieve, filter, combine and summarize information stored across relational database tables.
Write working SQL queries and produce a concise business analysis supported by accurate results.
Python and Pandas
Learn how to clean, transform, validate, explore and analyze datasets using practical Python and Pandas workflows.
Complete a documented data-cleaning and exploratory analysis workflow.
Power BI and Data Storytelling
Create business measures, professional visualizations and interactive dashboards that communicate meaningful insights.
Build and present an interactive dashboard based on a realistic business dataset.
Data Analyst Foundation Belt Assessment
Demonstrate your ability to apply SQL, Python, data preparation, visualization and business interpretation.
Achieve at least 70%. A maximum of two assessment attempts is available.
AI-Assisted Analytics and Capstone
Use AI responsibly to support analysis, validate AI-assisted results and combine your technical skills in a complete business project.
Produce and present an end-to-end capstone project with technical work, business interpretation and recommendations.
Learn More Without Feeling Overloaded
Your weekly activities are designed to fit within approximately 8–10 hours. DataCamp practice is included in these hours—it is not additional work.
Live Instructor Session
Concept explanation, demonstration, guided practice, questions and the weekly activity briefing.
Focused Lesson Content
Read only the essential concepts, examples and instructions required for the current week.
Guided Technical Practice
Complete selected exercises using LearnDash resources, guided datasets and assigned DataCamp activities.
Assignment and Review
Apply the weekly skill in a focused assignment, complete a short quiz and review the areas requiring more practice.
Progress Is Demonstrated Through Practical Work
Short quizzes that confirm understanding and decisions
Weekly guided exercises using realistic datasets
Focused assignments requiring independent application
Monthly projects that integrate the month’s skills
Foundation Belt Assessment after Month 3
Integrated capstone project completed during Month 4
Complete the Required Learning and Demonstrate Your Skills
To qualify for the SAI DataScience AI-Enabled Data Analyst Career Certification, you must complete the required Core Path, assignments, quizzes and capstone project, meet academic-integrity requirements, and achieve at least 70% in the Foundation Belt Assessment.
Begin With Month 1: SQL for Data Analysis
Follow the lessons in order, complete only the activities assigned for the current week and ask for support early whenever an instruction or technical issue is unclear.
Start Month 1 — SQL for Data Analysis
Begin with Week 1 to understand how analysts work with databases, where SQL is written and how to create your first SQL query.
Start Month 1 →