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Data Analytics Course

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Edoxi’s Data Analytics course is a 60-hour online training program covering top analytics tools like Python, SQL, Power BI, Advanced Excel and Statistics. Learn data cleaning, statistical analysis, data visualisation and generate actionable insights. Training includes 5 major projects and a capstone project. Upon completion, receive a CPD UK-accredited Data Analytics Certification. Enrol now to become a skilled Data Analyst!
Course Duration
60 hours
Corporate Days
5 Days
Learners Enrolled
500+
Module
9
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Course Rating
4.9
star-rating-4.9
Mode of Delivery
Online
Accredited by
CPD accredited provider

What Do You Learn from Edoxi's Data Analytics Training

Python Data Analysis Fundamentals
Master Pandas, NumPy, and Matplotlib. Build skills in data manipulation, cleaning, and visualisation using Jupyter Notebooks.
SQL Database Querying Skills
Write complex queries, joins, and CTEs. Extract insights from MySQL databases using window functions.
Power BI & Excel Dashboard Creation
Design interactive dashboards using Power Query. Transform raw data into compelling visual stories for stakeholders.
Statistical Analysis and Hypothesis Testing
Apply SciPy for A/B testing and p-value analysis. Make data-driven decisions using confidence intervals.
Data Cleaning and Transformation
Learn to handle missing values, outliers, and duplicates and master feature engineering and encoding techniques for analysis-ready datasets.
Real-World Project Implementation
Participate in e-commerce, healthcare, and finance projects and build a portfolio showcasing end-to-end analytics workflows.

About Our Online Data Analytics Course 

Edoxi’s 60-hour Data Analytics Course is designed to help you develop the practical skills needed to collect, clean, analyse, and interpret data for informed business decisions. Whether you’re a beginner starting from scratch or a professional looking to upskill, the course follows a structured learning path that takes you from fundamental data concepts to advanced analytics techniques.


The Data Analyst Course covers key areas such as data management, Python programming, SQL, statistical analysis, and dashboard development. Participants learn through a combination of expert-led instruction, interactive sessions, and practical exercises, allowing you to apply concepts as you progress.


Our live online Data Analytics training provides hands-on experience with industry-standard tools and real-world datasets sourced from platforms such as Kaggle and government portals. Students work on practical tasks including data cleaning with Pandas, writing SQL queries, analysing datasets, and creating Power BI & Excel dashboards.

This image illustrates the progression from Beginner to Expert Data Analyst in Edoxi's Data Analytics course.

For corporate teams, Edoxi offers a 5-day customised Data Analytics Corporate Training that can be delivered at your office, a hotel, or Edoxi’s training centre. Upon successful completion, you’ll receive a CPD UK-accredited Data Analytics Certification, providing formal recognition of your training. 


With practical exposure to Python, SQL, statistical analysis, Excel, Power BI, and real-world datasets, you can build a foundation for roles such as Data Analyst, BI Specialist, or Analytics Consultant across sectors including finance, healthcare, logistics, and e-commerce. Enrol now and build the practical data analytics skills you need to pursue data-driven career opportunities globally.


What is Data Analytics?


Data Analytics is the process of collecting, cleaning, analysing, and interpreting data to identify meaningful patterns, trends, and insights that support informed decision-making. It helps organisations transform raw data into useful information that can improve business performance, understand customer behaviour, identify opportunities, and solve problems. Data analytics involves using tools and techniques such as Excel, SQL, Python, Power BI, and statistical analysis to work with data effectively.

Key Features of Edoxi's Data Analytics Training

Real-World Dataset Exercises

Work with datasets from Kaggle, government portals, and Maven Analytics to apply data analytics concepts to realistic scenarios.

Comprehensive Learning Resources

Access Microsoft documentation, practice notebooks, Excel templates, SQL queries, Power BI files, and other supporting materials throughout the course.

Live Interactive Coding Sessions

Participate in instructor-led coding exercises covering data cleaning, SQL queries, statistical analysis, and dashboard development.

Progressive Learning Structure

Follow a structured curriculum that moves from data fundamentals to advanced analytics, with clearly defined learning milestones.

Industry-Standard Analytics Tools

Develop practical skills using Python, MySQL, Power BI, Excel, SciPy, and Seaborn.

End-to-End Capstone Project

Apply your learning to a complete analytics project covering data preparation, analysis, visualisation, and presentation.

Who Can Join Our Data Analytics Course?

Fresh Graduates and STEM Professionals

Recent graduates in commerce, engineering, IT, business management, or related disciplines seeking to launch careers.

Business and Marketing Analysts

Current analysts and marketing professionals who want to enhance their capabilities with Python, SQL, and Power BI for deeper data insights.

Finance and Operations Executives

Professionals in finance, operations, and logistics roles looking to leverage data analytics for forecasting, optimisation, and strategic decision-making.

IT and Software Engineers

Technical professionals aiming to expand their skillset into data analytics, combining programming knowledge with business intelligence capabilities.

Healthcare and Retail Staff

Industry professionals from healthcare, retail, and e-commerce sectors seeking to analyse operational data for improved efficiency and customer insights.

Career Transitioners

Individuals from any background with basic computer skills and logical thinking abilities are ready to transition into high-demand data analytics roles.

Data Analytics Course Modules

Module 1: Introduction to Data Analysis
  • Chapter 1.1: Fundamentals of Data Analysis

    • Lesson 1.1.1 What is Data Analysis?
    • Lesson 1.1.2 Types of Data: Structured vs Unstructured
    • Lesson 1.1.3 Importance and Applications in Industry
  • Chapter 1.2: Overview of the Data Analysis Lifecycle

    • Lesson 1.2.1 Data Analysis Process Overview (Ask → Prepare → Process → Analyze → Share → Act)
    • Lesson 1.2.2 Introduction to Analytical Tools (Excel, Python, SQL, Power BI)
  • Chapter 1.3: Setup and Initial Exploration

    • Lesson 1.3.1 Install Tools (Jupyter, Excel, SQL environment)
    • Lesson 1.3.2 Explore Datasets (e.g., Iris, Titanic, Sales Data)
Module 2: Data Collection & Cleaning
  • Chapter 2.1: Data Acquisition

    • Lesson 2.1.1 Data Sources: Surveys, Databases, APIs, Web Scraping
    • Lesson 2.1.2 Data Formats: CSV, JSON, XLS, TXT, HTML
  • Chapter 2.2: Data Cleaning Fundamentals

    • Lesson 2.2.1 Handling Missing Values
    • Lesson 2.2.2 Cleaning Techniques: Duplicates, Outliers, Data Type Conversions
    • Lesson 2.2.3 String and Date Cleaning
    • Lesson 2.2.4 Data Quality Assessment
  • Chapter 2.3: Hands-On Data Cleaning

    • Lesson 2.3.1 Use Pandas to Clean a Messy CSV File
    • Lesson 2.3.2 Excel: Filters, Conditional Formatting, Data Validation
    • Lesson 2.3.3 Power BI: Power Query Editor for ETL Process
    • Lesson 2.3.4 Assignment: Clean a Small Dataset and Explain Steps
Module 3: Exploratory Data Analysis (EDA)
  • Chapter 3.1: Descriptive Statistics

    • Lesson 3.1.1 Measures of Central Tendency: Mean, Median, Mode
    • Lesson 3.1.2 Measures of Dispersion: Variance, Standard Deviation
    • Lesson 3.1.3 Skewness and Kurtosis
  • Chapter 3.2: Data Visualisation Techniques

    • Lesson 3.2.1 Histograms, Boxplots, Scatterplots
    • Lesson 3.2.2 Heatmaps and Pairplots
  • Chapter 3.3: Feature & Correlation Analysis

    • Lesson 3.3.1 Correlation Analysis
    • Lesson 3.3.2 Feature Distribution and Summary
    • Lesson 3.3.3 Lab: Visualisations with Seaborn/Matplotlib
    • Lesson 3.3.4 Assignment: EDA and Mini-Report
Module 4: Data Wrangling & Transformation
  • Chapter 4.1: Data Structuring Techniques

    • Lesson 4.1.1 Merging, Joining, and Concatenation
    • Lesson 4.1.2 Reshaping Data: Pivot and Melt
  • Chapter 4.2: Feature Engineering

    • Lesson 4.2.1 Creating New Variables
    • Lesson 4.2.2 Encoding Categorical Variables
    • Lesson 4.2.3 Binning, Normalisation, and Scaling
    • Lesson 4.2.4 Lab: Data Preparation with Pandas
    • Lesson 4.2.5 Assignment: Clean, Merge, and Encode Data
Module 5: Data Analysis with SQL
  • Chapter 5.1: SQL for Analysts

    • Lesson 5.1.1 Introduction to Databases
    • Lesson 5.1.2 Writing SQL Queries
    • Lesson 5.1.3 Joins, Subqueries, and CTEs
    • Lesson 5.1.4 Aggregation & Grouping
    • Lesson 5.1.5 Window Functions and Case Statements
    • Lesson 5.1.6 Lab: Querying a Sample Database
Module 6: Introduction to Statistical Analysis
  • Chapter 6.1: Probability and Distribution Basics

    • Lesson 6.1.1 Probability and Common Distributions
    • Lesson 6.1.2 Central Tendency and Variability
  • Chapter 6.2: Hypothesis Testing

    • Lesson 6.2.1 t-Test, p-Value, and Statistical Significance
    • Lesson 6.2.2 Confidence Intervals
    • Lesson 6.2.3 Lab: Hypothesis Testing with SciPy
    • Lesson 6.2.4 Assignment: A/B Testing Case Study
Module 7: Data Visualisation & Storytelling
  • Chapter 7.1: Visualisation Principles

    • Lesson 7.1.1 Principles of Effective Data Visualisation
    • Lesson 7.1.2 Dashboard Design Concepts
  • Chapter 7.2: Tools for Visual Communication

    • Lesson 7.2.1 Excel Dashboards
    • Lesson 7.2.2 Power BI Dashboards
    • Lesson 7.2.3 Plotly, Seaborn, and Matplotlib for Storytelling
Module 8: Real-World Projects & Case Studies
  • Chapter 8.1: Domain-Specific Case Studies

    • Lesson 8.1.1 E-commerce Data Analysis
    • Lesson 8.1.2 Healthcare Data Analysis
    • Lesson 8.1.3 Finance or Sales Forecasting
    • Lesson 8.1.4 A/B Testing for Marketing Campaigns
    • Lesson 8.1.5 Customer Segmentation Techniques
Module 9: Capstone Project
  • Chapter 9.1: End-to-End Data Analysis

    • Lesson 9.1.1 Build the Full Pipeline: Clean → EDA → Model → Present
    • Lesson 9.1.2 Project Report and Presentation
    • Lesson 9.1.3 Peer and Instructor Review

Download Data Analytics Course Brochure

Real-World Projects in Our Data Analytics Course

Edoxi’s Online Data Analytics Course follows a project-based approach, giving you hands-on experience with authentic datasets from Kaggle, government repositories, and Maven Analytics. Key projects include;

Projects

  • E-commerce Customer Segmentation and Sales Analysis

    Analyse customer behaviour patterns using SQL and Pandas to segment audiences, identify purchasing trends, and create actionable insights for marketing strategies.

  • A/B Testing for Marketing Campaign Optimisation

    Design and execute statistical hypothesis testing on marketing data using SciPy and statsmodels to evaluate campaign effectiveness through p-value analysis.

  • Healthcare Data Analytics Dashboard

    Clean and transform medical datasets using Power Query, perform exploratory analysis with Python, and create interactive Power BI dashboards.

  • Financial Sales Forecasting Model

    Develop predictive analytics solutions using historical sales data, applying statistical methods and visualisation techniques to forecast business trends.

  • End-to-End Data Analytics Pipeline

    Complete a comprehensive data analysis workflow from raw data collection through cleaning, analysis, and presentation, demonstrating mastery of all tools.

Data Analytics Course Outcome and Career Opportunities

Edoxi’s Data Analytics Course provides a strong foundation for building a successful career in the rapidly growing international data analytics sector. By the end of the program, you will:

Course Outcome Image
Develop in-demand skills in data cleaning, analysis, visualisation, and reporting using tools like Python, SQL, Excel, and Power BI.
Qualify for roles across key industries such as finance, healthcare, e-commerce, and technology.
Gain a competitive edge in the international job market, where data-driven decision-making is increasingly vital.
Enhance career growth opportunities with certification that validates your analytical expertise.
Be well-positioned for high-demand roles such as Data Analyst, Business Intelligence Analyst, Reporting Specialist, and more.
Gain a Data Analytics Certification that showcases your capabilities to potential employers.

Career Opportunities After the Data Analytics Course

  • Data Analyst
  • Data Entry & Reporting Analyst
  • Business Data Analyst
  • Quantitative Research Analyst
  • Product Analytics Associate
  • KYC Data Analyst
  • Business Intelligence (BI) Analyst
  • Marketing/CRM Data Analyst
  • Operations Data Analyst
  • Data Engineer
  • Quantitative Analyst

Data Analytics Training Options

Online Training

  • 60-Hour Online Data Analytics Course

  • Interactive virtual coding sessions

  • Screen sharing for demonstrations

  • Cloud access to tools/datasets

  • Recorded sessions for revision

  • Learn at your own pace and convenience

Corporate Training

  • 5-Day Customised Data Analytics Training

  • Curriculum as per your requirements

  • Flexible venue: Hotel/Client premises/Edoxi

  • Food and refreshments provided

  • Visa and travel arrangements

  • Team-based business-aligned projects

  • Pre and Post-Assessment Reports

Do You Want a Customised Training for Data Analytics ?

Get expert assistance in getting your Data Analytics Course customised!

How to Get Certified in Data Analytics ?

Here’s a four-step guide to becoming a certified Data Analytics professional.

Do You Want to be a Certified Professional in Data Analytics?

Join Edoxi’s Data Analytics Course

Why Choose Edoxi For Data Analytics Course

Edoxi is considered the leading training institute offering 700+ courses for students, professionals and corporates. Here are a few reasons why you should choose Edoxi for the Data Analytics Course;

Practical Training Approach

Learn by applying concepts to realistic datasets and business scenarios rather than relying solely on theoretical instruction.

Portfolio Development

Build five major data analytics projects using tools such as Python, SQL, Power BI, and Advanced Excel to demonstrate your practical capabilities.

Expert-Led Learning

Learn through instructor guidance, live demonstrations, interactive sessions, and feedback designed to help you understand and apply analytics concepts effectively.

Career-Relevant Curriculum

Develop technical and analytical skills aligned with the requirements of modern data-driven workplaces across industries.

Continuous Learning Support

Get access to updated learning materials, relevant tools, practical guidance, and support throughout your training journey.

CPD-UK Accredited Certification

Receive a CPD-UK-accredited course certification upon successful completion, providing formal recognition of your data analytics training.

Suitable for Different Skill Levels

Whether you are a beginner, career switcher, or working professional, the structured training helps you build your skills progressively.

Global Presence

Benefit from Edoxi’s international presence across Dubai, Qatar, London, and Kuwait, with training designed to meet the evolving needs of professionals and organisations across global markets.

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Edoxi is Recommended by 95% of our Students

Meet Our Mentor

Our mentors are leaders and experts in their fields. They can challenge and guide you on your road to success!

mentor-image

Nahid S

Nahid S. is an experienced educator with 8+ years of expertise in academia, training, and software development. Skilled in curriculum design, interactive training, and mentorship, she has equipped learners with hands-on skills in data analytics, data science, cloud computing, and software engineering. Nahid is an AWS Academy Accredited Educator, AWS Certified Solutions Architect – Associate, Microsoft Certified: Azure Fundamentals, and Google Certified Educator (Level 1). She brings a strong technical foundation and industry credibility to the classroom, blending theoretical knowledge with practical applications.

Nahid has delivered engaging lectures and practical sessions across core and elective subjects, including Cloud Computing, Python, Machine Learning, and Data Science. Nahid has designed and implemented industry-relevant training programs that boost employability. With a strong focus on student development, she has provided mentorship in projects, internships, and career planning while organising workshops, seminars, and guest lectures to bridge the gap between academia and industry.

Inspiring Words from Satisfied Clients

FAQ

Is this course suitable for beginners?
Yes. It builds skills from foundational concepts up through advanced tools with step-by-step support.
Are there any prerequisites to join?
No prior experience is required, just basic computer literacy and an interest in data.
What is the average salary for data analysts?
$55,000 to $120,000 annually, depending on experience, location, and industry (with higher pay in tech, finance, and healthcare).
Will I get hands-on experience?
Yes. You will work with real-world datasets across 5 major projects and 1 capstone project using Python, SQL, Power BI, and Advanced Excel.
What certification will I receive?
You will receive the Edoxi Course Completion Certificate and a CPD UK-accredited certificate (40 CPD hours).
Is coding required for this course?
No prior coding experience is needed. The course teaches Python and SQL from the ground up, focusing on practical data manipulation and analysis.
How long does it take to complete the course?
The program includes 60 hours of total training. Overall duration depends on whether you choose weekday or weekend schedules.
What job roles can I apply for after completing this course?
You can apply for roles such as Data Analyst, Junior Data Scientist, Business Intelligence (BI) Analyst, Data Operations Analyst, and Financial Analyst.
Are class recordings provided if I miss a live session?
Yes, recordings of live online sessions are typically provided so you can catch up or review concepts at your own pace.
Does the course offer job placement assistance?
Yes, training includes resume building, portfolio creation using the capstone projects, and interview preparation guidance.