Data Analyst Course

Data Analyst skill advancement in 60 hours

Globally recognised certification

Copilot & Automation Sandbox for work efficiency

12 immersive modules & professional capstone projects

Flexible learning modes & easy payment options

4.85/5

5568 Enrolled

Overview

What our training includes:

Trains participants in Excel, SQL, Power BI, and Python
Pairs each module with an industry simulation grounded in real business scenarios
Covers data manipulation, DAX modelling, and report sharing via Power BI Service
Works through Python and Pandas before moving into statistics and hypothesis testing
Closes with a capstone project that brings together analysis, dashboards, and reporting

Learning Objectives

After finishing the course, individuals will be able to:

Apply Excel functions and PivotTables to analyse business data

Write SQL queries to extract and aggregate structured data

Build Power BI dashboards using DAX and visual filters

Use Microsoft Copilot and Fabric for AI-assisted analytics

Clean and analyse datasets in Python using Pandas

Conduct statistical analysis and hypothesis testing for business decisions

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Overall ratings by our students

Upcoming sessions

Our Trainers

Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.

We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.

KHDA Certificate

Earn a KHDA attested Course Certificate. The Knowledge and Human Development Authority (KHDA) is the educational quality assurance and regulatory authority of the Government of Dubai, United Arab Emirates.

Learners Point Certificate

Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.

Related courses

Curriculum

Introduction to Python and Jupyter Notebooks
Variables, data types, and control flow
Functions and libraries in Python
Working with data (Lists, Tuples, Dictionaries)
Data structures and algorithms basics

Industry Simulation – Module 1:

Project Name: Data Processing Automation
Description: Automate report filtering tasks using Python to process raw business data, demonstrating basic Python syntax and data manipulation techniques.

Introduction to Excel for business analysis
Using formulas and functions for data manipulation
Advanced Excel functionalities
PivotTables, charts, and graphs for reporting
Data cleaning and visualization with Excel

Industry Simulation – Module 2:

Project Name: Business Data Report Generation
Description: Use Excel to analyze business data, generate key reports, and visualize the outcomes for decision-making

Introduction to SQL and basic queries
Filtering and sorting data
Joins (INNER JOIN, LEFT JOIN, etc.)
Aggregating data using GROUP BY and HAVING
Subqueries and set operations

Industry Simulation – Module 3:

Project Name: SQL Query for Sales Data Analysis
Description: Write SQL queries to extract and manipulate sales data for analysis, preparing it for further insights and reporting.

Getting started with Power BI Desktop
Importing data from Excel, SQL, and other sources
Creating basic visualizations (charts, graphs, tables)
Building a simple report
Using filters, slicers, and hierarchies

Industry Simulation – Module 4:

Project Name: Power BI Sales Dashboard
Description: Create a basic Power BI dashboard visualizing key sales metrics like total sales, sales by region, and monthly trends.

Data modeling basics in Power BI
Introduction to DAX (Data Analysis Expressions)
Building calculated columns and measures
Aggregating data using DAX
Creating more advanced visualizations using DAX

Industry Simulation – Module 5:

Project Name: Sales Reporting with DAX
Description: Use DAX in Power BI to create calculated columns and measures, building a comprehensive sales report.

Designing and sharing advanced visuals
Working with Power BI Servic
Publishing reports and dashboards to the cloud
Collaborating with team members in Power BI Service
Creating interactive reports

Industry Simulation – Module 6:

Project Name: Interactive Sales Dashboard
Description: Design and share an interactive sales dashboard in Power BI, integrating data from multiple sources

AI-powered features in Power BI
Using Copilot in Power BI
Dataflow management with Microsoft Fabric
Predictive analytics and forecasting
Best practices for AI-driven analytics in Power BI

Industry Simulation – Module 7:

Project Name: AI-Powered Analytics Implementation
Description: Implement AI-powered features in Power BI, leveraging Copilot and Microsoft Fabric for real-time data integration and predictive analytics.

Advanced data analysis with Python libraries (Pandas, NumPy, etc.)
Exploratory data analysis (EDA) techniques
Handling missing data and outliers
Data transformations and aggregations

Industry Simulation – Module 8:

Project Name: Automated Data Cleaning in Python
Description: Use Python to clean, transform, and analyze datasets, automating the data preparation process for further analysis.

NumPy for numerical computations
Jupyter for interactive data analysis
Matrix operations and linear algebra in NumPy
Handling large datasets with NumPy

Industry Simulation – Module 9:

Project Name: Data Exploration with NumPy
Description: Explore a large dataset using NumPy and Jupyter for data analysis, highlighting key insights and trends.

Dataframes in Pandas
Data wrangling and cleaning
Merging, reshaping, and slicing data
Groupby and aggregation techniques

Industry Simulation – Module 10:

Project Name: Data Cleaning & Transformation with Pandas
Description: Use Pandas to clean, manipulate, and merge data, preparing it for analysis and visualization.

Basic statistical analysis with Pandas
Probability distributions
Statistical inference
Hypothesis testing techniques

Industry Simulation – Module 11:

Project Name: Statistical Analysis of Business Data
Description: Perform statistical analysis on a business dataset, calculating key metrics like mean, median, variance, and standard deviation.

A/B testing and significance testing
Confidence intervals and p-values
Statistical power and effect size
Practical applications in business decision-making

Industry Simulation – Module 12:

Project Name: A/B Testing for E-commerce
Description: Conduct an A/B test for an e-commerce business and evaluate the results using t-tests and confidence intervals.

Project Name: Integrated Data Analysis & Reporting Solution
Objective: Participants will apply all learned skills by analyzing a dataset and building a comprehensive business report or dashboard that integrates data manipulation, visualization, and predictive modeling

Project Name: AI-Powered Reporting Tool
Description: Design an AI-powered reporting tool that automates data extraction and analysis, integrating Power BI and Tableau for dynamic reporting.

Project Name: AI-Enhanced Data Analysis for Business Applications
Description: Simulate data analysis tasks relevant to domains like finance, marketing, operations, etc., using AI-powered tools for business insight generation.

Frequently asked questions

The Data Analyst Training covers four primary tools:

Microsoft Excel
SQL
Power BI
Python

The SQL modules address data extraction, filtering, joins, and aggregation. Power BI sessions extend into DAX modelling, report publishing via Power BI Service, and AI-assisted analytics through Microsoft Copilot and Fabric. Python modules cover Pandas, NumPy, and Jupyter Notebooks, with dedicated sessions on exploratory data analysis, data wrangling, descriptive statistics, and hypothesis testing.

The training is a credible signal of technical competence in a field where employer expectations are rising. According to the World Economic Forum's Future of Jobs Report 2026, data analysts and scientists rank among the top ten fastest-growing roles globally over the next five years. In the UAE and GCC, ongoing digital transformation across government, banking, and retail is accelerating demand for professionals with verified skills in tools such as SQL, Power BI, and Python. Certification provides a verifiable, structured basis for that verification. (World Economic Forum, 2026)

Completing this certification course opens pathways to roles such as:

Data Analyst
Business Intelligence Analyst
Reporting Analyst
Junior Data Scientist

These positions exist across finance, technology, retail, operations, and healthcare sectors. Professionals with combined competence in SQL, Power BI, Python, and applied statistics are well-placed for roles involving performance reporting, trend analysis, and data-supported recommendations.

No prior programming experience is required. The course is designed for junior and mid-level professionals who may have limited or no technical background. Python is introduced from the ground up, beginning with variables, data types, control flow, and functions before progressing to libraries such as Pandas and NumPy. Professionals with a basic familiarity with Excel will find the early modules straightforward, and the simulation projects provide structured practice at each stage before the difficulty level increases.

A Data Analyst primarily focuses on collecting, cleaning, and interpreting datasets to address specific business questions, often using tools like SQL, Excel, and Python. On the other hand, a Business Intelligence Analyst is more involved with reporting platforms, such as Power BI, to create dashboards, track key performance indicators (KPIs), and support strategic planning.

In practice, there is a significant overlap between these two roles. The Data Analyst Training Course encompasses both areas, allowing graduates the flexibility to pursue either analytical or reporting-focused positions as their careers progress.

Yes, this course is structured keeping the working professionals in mind. The program is delivered in a format that accommodates participants who cannot commit to full-day schedules. The 12-module structure allows learners to progress in a logical sequence without needing extended time away from work.

Each simulation project reinforces one module's content, so there is no requirement to retain everything before moving forward. Professionals from non-technical backgrounds have completed this training alongside active roles in finance, operations, and management.

Learners Point structures the Data Analyst Training across distinctive modules. Each of these modules is paired with an industry simulation project. This means every concept is immediately applied to a practical task, such as building a Power BI sales dashboard, writing SQL queries against real datasets, or conducting an A/B test for an e-commerce scenario.

The program ends with a consolidated capstone project designed to replicate the kind of deliverable an analyst would be expected to produce in a professional business environment, making the learning directly transferable to workplace tasks.