Certified Data Analyst Professional
A project-based, 120-hour certification that builds a complete, job-ready analytics toolkit — from Excel, SQL and statistics to Power BI, Tableau and Looker dashboards, data storytelling, and AI-assisted analysis on Google Cloud — finished with a real capstone.
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Course Info
- Type
- Certification
- Subject
- Individual & Professional Certification
- Duration
- 120 Hours
- Course code
- CDAP
- Prerequisites
- Comfort with basic computing; foundational programs available if needed.
Delivery
- Live-virtual — Instructor-led online cohorts.
- On-site — In-person at your premises or ours.
- Self-paced — Learn on your own schedule.
Tools
- Excel
- Power BI
- Tableau
- Looker
- MySQL
What you'll learn
The Certified Data Analyst Professional (CDAP) program is a practical, project-based training designed to build a strong foundation in data analysis using industry-leading tools such as Excel, Power BI, MySQL, Tableau, and Looker Studio. The program covers the entire data analysis pipeline—from data collection and transformation to modeling, visualization, and storytelling—enabling participants to extract insights and communicate them effectively. Through a hands-on approach, participants gain practical experience across the entire data analysis lifecycle, culminating in a real-world capstone project. Graduates will be equipped with real-world skills required for roles like Data Analyst and will be ready to progress into more advanced data and AI roles with a job-ready portfolio of applied projects.
No specific prerequisites are required to enroll, but basic familiarity with math and statistics will enhance your learning experience. Familiarity with basic concepts in math and statistics is optional but helpful.
How you'll learn
- Instructor-Led Training (ILT): Participate in interactive, classroom-based sessions led by experienced industry professionals for an immersive learning experience.
- Virtual Instructor-Led Training (VILT): Join live online classes from anywhere, offering flexibility without compromising interactivity and mentorship.
- Aspiring Data AnalystsIndividuals seeking to build a strong foundation in data handling, visualization, and analytical thinking using tools like Excel, Power BI, and SQL.
- Developers and Technical EngineersSoftware engineers or IT professionals looking to expand into data analytics and business intelligence roles.
- Business and Analytics ProfessionalsDecision-makers, analysts, and team leads who want to leverage data for smarter business insights and data-driven strategies.
- Analyze, clean, and transform data using Excel, Power BI, and SQL.
- Design and query relational databases with MySQL.
- Apply statistical techniques to uncover insights and support decisions.
- Build interactive dashboards and communicate data through visual storytelling.
- Complete real-world projects to showcase job-ready data analysis skills.
Excel Projects
- Project 1: Build a clean, validated employee tracker with summary statistics and formatted visuals.
- Project 2: Build a professional Excel-based sales dashboard combining Power Query, PivotTables, Power Pivot modeling, and DAX calculations for interactive reporting and analysis.
- Project 3: Build a customer churn prediction sheet using formulas and dashboards to highlight risk factors and monthly trends.
Power BI Projects
- Project 4: Marketing Data Cleanup & Transformation — Use Power Query to standardize and clean raw campaign data from multiple sources.
- Project 5: HR Analytics Dashboard using Power BI Data Models & DAX.
- Project 6: Executive Sales Dashboard with Storytelling & Interactivity.
- Project 7: Marketing Scenario Dashboard with What-If Parameters.
Looker Data Studio Projects
- Project 8: Looker Data Studio E-commerce Dashboard.
Tableau Projects
- Project 9: Tableau Business Performance Metrics.
MySQL Projects
- Project 10: Design E-commerce Database.
- Project 11: E-commerce System Database Analysis.
- Project 12: Lynda Courses Database Analysis.
Capstone Project
- A comprehensive End-to-End Data Analysis Solution that integrates all skills acquired to solve a real-world problem, building a portfolio that sets you apart in the job market.
- Program Hours
- 120 Hours
- Corporate Training
- 16 full days, with each day lasting 7–8 hours.
- Individual Learners
- 4-month program with 2 sessions per week (4 hours each), OR 5-month program with 1 session per week (6 hours each).
- Locations
- USA (Newark, Delaware); Saudi Arabia (Riyadh); UAE (Jumeirah Lake Towers, Dubai — in partnership with Elbadya Quantum); Egypt (New Cairo, Nasr City, and Mohandessin/Giza).
Upon successful completion of the Certified Data Analyst Professional (CDAP) program, participants will receive an official Certificate of Completion from Epsilon AI – Delaware, USA, recognizing their proficiency in data analysis, statistics, Excel, Power BI, SQL, and data visualization. The program is delivered in alignment with international standards, including ISO 21001 and ISO 9001, and follows globally recognized frameworks such as IACET and CPD, ensuring a high-quality, industry-relevant learning experience. All graduates receive a digitally authenticated certificate containing a unique Certificate ID and personal EPSILON ID, enabling instant, secure online verification—ideal for professional portfolios, LinkedIn profiles, and employer validation. In addition, a prestigious hardcopy certificate is issued, printed with advanced security and branding features including a unique serial number and verification code, a gold-embossed seal with authorized EPSILON AI signatures, and UV-printed security elements for enhanced authenticity and protection against forgery.
- Attend a minimum of 80% of live instructional sessions.
- Achieve a minimum score of 80% on the final examination.
- Successfully complete and present the Capstone Project.
Program Curriculum
- What is Data Analysis?
- Business Importance and Real-World Use Cases
- Data Analysis Process: Collect, Clean, Explore, Model, Visualize
- Data Types & Measurement Levels
- Role & Skills of a Data Analyst
- Introduction to Descriptive Statistics
- Types of Data: Categorical vs. Numerical
- Levels of Measurement: Nominal, Ordinal, Interval, Ratio
- Graphs for Categorical Data: Bar Charts, Pie Charts
- Frequency Distribution Tables
- Understanding Relationships Between Variables
- Measures of Central Tendency: Mean, Median, Mode
- Measures of Dispersion: Range, Variance, Standard Deviation
- Understanding Skewness & Shape of Distributions
- Co-Variance & Correlation: Identifying patterns and relationships
- Using Excel's Analysis ToolPak: Descriptive Statistics Summary; Mean, Median, Mode; Range, Minimum, Maximum; Skewness, Standard Deviation
- Introduction to Inferential Statistics
- Types of Distributions: Normal, t, Chi-square, etc.
- Central Limit Theorem & Sampling Distributions
- Estimators vs. Estimates
- Confidence Intervals & Margin of Error
- Basics of Hypothesis Testing (One-sample examples)
- Excel Fundamentals: Navigating the interface (ribbons, worksheets, cells, and ranges); workbook structure, data entry techniques, and formatting best practices
- Data Handling Basics: Sorting and filtering (single and multi-level); freezing panes, hiding/unhiding rows & columns; creating structured tables and understanding table formatting
- Validation & Error Prevention: Data validation (dropdowns, input restrictions); removing duplicates and text-to-columns usage
- Introduction to Excel Functions: Arithmetic functions (SUM, AVERAGE, MIN, MAX, COUNT); basic logic (IF, AND, OR)
- Introduction to Conditional Formatting: Visual cues (color scales, icon sets, data bars)
- Basic Data Visualization: Creating bar, column, line, and pie charts; formatting chart elements and layout
- PROJECT #1: Build a clean, validated employee tracker with summary statistics and formatted visuals
- Advanced Function Usage — Text functions: CONCATENATE, TEXTJOIN, LEFT, RIGHT, MID, LEN, FIND, SUBSTITUTE
- Logical and error functions: Nested IFs, IFERROR, IFS
- Lookup functions: VLOOKUP, HLOOKUP, INDEX-MATCH, XLOOKUP
- Statistical functions: MEDIAN, MODE, STDEV, VAR, RANK, LARGE, SMALL
- Date/time functions: TODAY, NOW, DATEDIF, NETWORKDAYS, EOMONTH, TEXT
- Array Formulas & Dynamic Arrays: Understanding and applying FILTER, SORT, UNIQUE
- Pivot Tables & Pivot Charts: Creating, grouping, summarizing, and customizing pivot tables; GETPIVOTDATA for structured reference and calculated fields; incorporating slicers and timelines for interactivity
- Advanced Data Visualization: Building combo charts, histogram, waterfall charts; enhancing dashboards with conditional formatting and visual indicators
- Power Query in Excel: Importing data from multiple sources (Excel, CSV, Web, databases); transforming data (split, clean, filter, fill, append, merge); managing nulls, text cleansing, conditional columns
- Data Modeling with Power Pivot: Creating relationships and Star Schema Structure; calculated columns vs. measures and KPI creation
- DAX Essentials within Excel: Using DAX for dynamic calculations; Time Intelligence functions (YTD, MTD, SAMEPERIODLASTYEAR); understanding row vs. filter context and using VAR for optimization
- PROJECT #2: Build a professional Excel-based sales dashboard combining Power Query, PivotTables, Power Pivot modeling, and DAX calculations for interactive reporting and analysis
- PROJECT #3: Build a customer churn prediction sheet using formulas and dashboards to highlight risk factors and monthly trends
- A comprehensive business case requiring full use of Excel tools: Power Query, PivotTables, Power Pivot, DAX, and advanced visualizations. The final delivery is an executive-level dashboard simulating a multi-department performance analysis.
- Power Query Fundamentals: Interface overview and workflow structure; connecting to diverse data sources (Excel, CSV, web, APIs, SQL, and more)
- Data Transformation Techniques: Filtering, sorting, and removing duplicates; splitting columns and replacing values; cleaning text, trimming whitespace, and renaming columns; handling missing data and data profiling
- Advanced Operations: Grouping, pivoting, and unpivoting data; appending and merging queries; performing advanced joins (Inner, Left, Right, Full); calculating date differences and text manipulations
- Custom Logic with M Language: Read and write basic M code; modify queries using the Advanced Editor; apply custom transformations using M functions; debug and optimize M code for better performance
- PROJECT #4: Marketing Data Cleanup & Transformation — Use Power Query to standardize and clean raw campaign data from multiple sources
- Data Modeling Principles: Star schema vs. snowflake schema design; building and managing relationships (one-to-many, many-to-many)
- DAX Fundamentals: Syntax, operators, calculated columns, and measures; common functions (SUM, COUNT, AVERAGE, CALCULATE)
- Advanced DAX Techniques: Time intelligence (YTD, MTD, SAMEPERIODLASTYEAR); aggregation with iterators (SUMX, AVERAGEX); context logic (Row vs. Filter Context, Variables VAR); filter manipulation (FILTER, ALL, SELECTEDVALUE)
- Performance KPIs & Metrics Design
- PROJECT #5: HR Analytics Dashboard using Power BI Data Models & DAX
- Visual Development with Power BI Desktop: Mastering interface components (home, insert, modeling, and view tabs); using visual elements (bar, pie, line, combo, tree, gauge, maps)
- Interactivity Features: Filters, slicers, bookmarks, drill-through, tooltips; creating navigation and layered user experiences
- Data Storytelling Best Practices: Designing with purpose (layout principles, user journey, hierarchy); framing business questions into visual insights
- PROJECT #6: Executive Sales Dashboard with Storytelling & Interactivity
- Power BI Cloud Platform Overview: Publishing reports and dashboards; dataset refresh and scheduled updates
- Workspace & Permissions Management: Creating and managing workspaces; sharing reports securely and collaborating in teams
- What-If Analysis Development: Parameter creation and dynamic visuals for simulation
- PROJECT #7: Marketing Scenario Dashboard with What-If Parameters
- Deliver a full-scale business intelligence report combining Power Query, Data Modeling, and DAX, published on Power BI Service, including interactivity, navigation, and simulation features. Final delivery includes executive presentation.
- Connecting to Google Sheets, BigQuery, SQL
- Scorecards, Charts, Filters, Drilldowns
- PROJECT #8: Looker Data Studio E-commerce Dashboard
- Navigation & Visual Design (Bar, Line, Map, Custom)
- Filters, Highlights, Storytelling Features
- PROJECT #9: Tableau Business Performance Metrics
- Power Automate for Analysts: Automating routine data workflows from Excel, SharePoint, Forms, etc.; triggers, connectors, and logic flows; integration with Microsoft ecosystem
- Using ChatGPT & AI Tools: Prompt engineering for data exploration and summarization; text classification, entity extraction, and data cleaning with GPT; building ChatGPT plug-ins and Excel GPT add-ins for analysis
- Relational Database Concepts (RDBMS): Database design; tables, columns and data types; relationships (One-To-Many & Many-To-Many)
- MySQL for Data Science: MySQL Workbench; CRUD Operations; selecting data; filtering data; ordering data; limiting data; Aggregate Functions; grouping data; subqueries; date and time management; inserting new data; updating data; deleting data
- Database connectivity and data manipulation using Python
- ACTIVITY: Design database structure like Facebook, Talabat, and YouTube
- PROJECT #10: Design E-commerce Database
- PROJECT #11: E-commerce System Database Analysis
- PROJECT #12: Lynda Courses Database Analysis
- Cloud Overview: AWS, Azure, GCP
- Data Integration & Analytics Tools
- Foundations — Cloud & Data Analytics Basics: What is cloud computing? (IaaS vs PaaS vs SaaS, multi-cloud vs single cloud); why analysts need the cloud (scalability, cost efficiency, collaboration, access to big data); GCP overview and core services (compute, storage, databases, networking, IAM); setting up a GCP account & understanding billing (covered by the Free GCP Account Setup and Trial Credits)
- Data Storage & Ingestion on GCP: Cloud Storage (buckets, file formats: CSV, Parquet, Avro); Cloud SQL (relational DB for analysts); BigQuery introduction (the core analyst tool); data ingestion tools (Pub/Sub, Dataflow basics, Dataprep, importing from external sources such as Sheets and APIs)
- BigQuery for Analysts (Core Module): BigQuery architecture (serverless, columnar storage, separation of computing & storage); writing efficient SQL in BigQuery (standard SQL, nested fields, arrays); partitioning & clustering for cost optimization; query performance optimization & pricing model (on-demand vs flat-rate). Done within the BigQuery Sandbox and Always Free Tier.
- Data Transformation & Workflow Orchestration: Introduction to Dataform (ETL/ELT pipelines for analysts); Dataprep for wrangling data without heavy coding; Cloud Composer (Airflow in GCP) for scheduling workflows; example daily pipeline (load raw CSV → clean & transform → BigQuery table → dashboard)
- Important Note on Cost: This curriculum is designed to be completed for free using Google Cloud's generous free tier and initial credits, with guidance on which services are always free and how to monitor usage and set up alerts for a worry-free learning journey.
- This final capstone simulates a real business scenario that requires participants to apply the complete data analysis lifecycle — from raw data ingestion to actionable insights presentation — across the different tools covered in the program.
- Deliverable: A multi-platform dashboard
- Deliverable: A data strategy summary document
- Deliverable: A recorded or live executive presentation simulating real-world stakeholder engagement
Frequently asked questions
How much does the program cost?
Pricing depends on the format you choose — online, onsite, or a corporate cohort — and any current offers. Fill in the registration form on this page and an Epsilon team member will contact you with the exact price and the options that fit you.
When does the next cohort start?
New cohorts open regularly across online and onsite formats. Fill in the registration form and our team will contact you with the next available start dates that fit your schedule.
Is the program online or onsite, and in which language?
Both — Epsilon runs live, instructor-led sessions online and onsite, plus dedicated corporate cohorts. Programs are delivered in English and Arabic, with bilingual materials and instructor support. Tell us your preference in the registration form.
What certificate will I receive?
A globally accredited certificate from Epsilon AI Learning — USA, carrying a unique Certificate ID and Epsilon ID. It is awarded on 80% attendance, an 80% final exam, and a completed capstone project, and it is verifiable online.
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Continue your pathway
At Epsilon AI Learning, we believe learning should be practical, modular, and aligned with your career growth—starting with strong foundations like those developed in the CDAP program. CDAP is part of our Top-Up Certifications pathway, designed to help you build essential skills in data analysis and progress smoothly into advanced, role-specific specializations. Each certification builds on the last, empowering you to advance step-by-step into high-demand data roles across industries.
Data / Business Analyst
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Advance after 3 dashboard / reporting projects
Led by Epsilon's expert instructors
Every program is delivered by practitioners who ship AI and analytics in industry — the same team across all Epsilon programs.
Where our graduates work
A sample of the employers hiring Epsilon Learning graduates across the region and beyond.
Earning your accredited certificate
To receive the accredited certificate you must pass both the placement test and the practical test with at least 80%, and complete the program fees.
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