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Data Analytics Course in London

Businesswoman analyzing charts during an Excel course in London
Edoxi’s Data Analytics Course in London is a 60-hour hands-on training program that teaches you how to collect, clean, analyse, and interpret data. You’ll work with real-world datasets and gain practical experience using top data tools like Excel, Power BI, Python, and SQL. Learn to create live Power BI dashboards, automate reports, write Python scripts, and develop SQL queries to support data-driven business decisions. Enrol now and gain in-demand data analytics skills in London.
Course Duration
60 hours
Corporate Days
7 Days
Learners Enrolled
100+
Modules
4
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Course Rating
4.9
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Mode of Delivery
Online
Offline
Certification by

What You'll Learn from the Data Analytics Training?

Advanced Excel Functions and Formulas
You will learn VLOOKUP, XLOOKUP, and conditional formatting to transform raw data into actionable insights for business analysis.
Power BI Dashboard Development
You will create interactive visualisations and reports using DAX expressions and Power Query for effective data storytelling.
Python Programming for Data Analysis
You will utilise Pandas, NumPy, Matplotlib, and Seaborn libraries for exploratory data analysis and statistical visualisation.
SQL Query Optimisation
You will design efficient SQL joins and queries to extract valuable information from relational databases for business intelligence.
Data Cleaning and Preparation
You will learn techniques to identify and handle missing values, outliers, and inconsistencies for reliable analytical outcomes.
Data Modelling and Interpretation
You will learn to apply analytical frameworks to transform complex datasets into structured insights for strategic decision-making.

About Our Data Analytics Training in London

Data Analytics Course in London delivered by Edoxi Training Ltd is a practical, industry-focused training designed to meet the rising demand for data skills across the UK. This 60-hour comprehensive Data Analytics Course training equips you with competencies in widely used tools like Excel, Power BI, Python, and MySQL. This course caters to a wide range of learners, including students, fresh graduates, working professionals, and career switchers. 

Edoxi’s Data Analytics Course emphasises hands-on learning through practical exercises and projects using real-world datasets. You will gain deep insights into how data analytics is applied to solve business problems, improve operations, and drive strategic decision-making. Our expert trainers will equip you with skills to handle real-world data challenges across various sectors, including finance, healthcare, technology, and retail.

Throughout the Course, you will engage in live coding sessions, build interactive dashboards, automate reporting systems, and write efficient SQL queries. With flexible delivery modes including Classroom Training, Live Online Training, and Corporate Training, Edoxi ensures that you receive a personalised and immersive educational experience. 

Upon successful completion, you will receive a Data Analytics Certification from Edoxi. This certification demonstrates your skills and helps you pursue roles such as Data Analyst, BI Developer, Analytics Consultant, and more in the thriving data industry in London. Enrol in our Data Analyst Course in London and gain in-demand data skills with Edoxi’s Data Analytics Course in London for a future-proof career.

Features of the Data Analytics Course

Real-World Dataset Practice

Work with authentic business datasets from various industries to develop practical analysis skills applicable to real scenarios.

Interactive Excel Templates

Access professionally designed Excel templates and workbooks for immediate application in professional environments.

Power BI Report Building

Create complete dashboards and reports using industry-standard visualisation techniques and best practices.

Python Notebook Exercises

Develop programming skills through guided Jupyter notebooks with step-by-step data analysis workflows.

SQL Query Practice

Practice writing and optimising database queries through interactive workshops with relational database systems.

Live Coding Sessions

Participate in instructor-led coding demonstrations that break down complex concepts into manageable techniques.

Who Can Join Our Data Analytics Course in London?

Students and Fresh Graduates

University students and recent graduates looking to gain practical data skills to enhance employability in the competitive London job market.

Business Analysts and Reporting Professionals

Those in charge of creating reports and extracting insights from company data who want to enhance their technical capabilities.

Marketing and Sales Professionals

Team members looking to better understand customer data, campaign performance, and market trends through analytical methods.

Finance Officers and Accounting Staff

Financial professionals seeking to improve forecasting, budgeting, and financial analysis through data-driven approaches.

IT Professionals and Developers

Technical staff wanting to add data analytics skills to their existing programming or system administration knowledge.

Project Managers and Team Leaders

Decision-makers who need to understand and leverage data for project planning, resource allocation, and performance tracking.

Data Analytics Course Modules

Module I: Advanced Microsoft Excel
  • Chapter 1.1: Excel Essentials and Cell Referencing

    • Lesson 1.1.1: Recall and overview of basic Excel functions
    • Lesson 1.1.2: Understanding cell references: Relative, Absolute, Mixed
    • Lesson 1.1.3: Circular and 3D cell references
    • Lesson 1.1.4: Custom number formatting techniques
  • Chapter 1.2: Functions and Conditional Expressions

    • Lesson 1.2.1: Date and time functions
    • Lesson 1.2.2: Text and database functions
    • Lesson 1.2.3: Writing conditional expressions with IF
    • Lesson 1.2.4: Logical functions: AND, OR, NOT
    • Lesson 1.2.5: Combining IF with AND/OR
    • Lesson 1.2.6: Power functions: COUNTIF, COUNTIFS, SUMIF, SUMIFS, SUMPRODUCT
  • Chapter 1.3: Lookup and Reference Functions

    • Lesson 1.3.1: VLOOKUP and HLOOKUP basics
    • Lesson 1.3.2: MATCH and INDEX functions
    • Lesson 1.3.3: Nested and dynamic VLOOKUPs
    • Lesson 1.3.4: Using VLOOKUP for multi-sheet data consolidation
    • Lesson 1.3.5: XLOOKUP features and usage
  • Chapter 1.4: Data Validation and Formatting

    • Lesson 1.4.1: Advanced data validation techniques
    • Lesson 1.4.2: Dynamic and dependent drop-down lists
    • Lesson 1.4.3: Conditional formatting for rows, columns, and wildcards
    • Lesson 1.4.4: Working with Excel templates
    • Lesson 1.4.5: Advanced table sorting and filtering
  • Chapter 1.5: Automation and Analysis Tools

    • Lesson 1.5.1: Macros - recording, editing, and automation
    • Lesson 1.5.2: Scenario tools - What-If, Goal Seek, Solver, Scenario Manager
    • Lesson 1.5.3: Key Excel features - Flash Fill, Sparklines, Remove Duplicates, Freeze Panes, Sheet Protection
  • Chapter 1.6: Excel Capstone

    • Lesson 1.6.1: Review of core Excel concepts
    • Lesson 1.6.2: Final project using Excel
Module 2: Microsoft Power BI
  • Chapter 2.1: Introduction to Self-Service BI

    • Lesson 2.1.1: Key concepts: BI, Data Analysis, Data Visualisation
    • Lesson 2.1.2: Overview of Microsoft BI tools
  • Chapter 2.2: Getting Started with Power BI

    • Lesson 2.2.1: Power BI components and architecture
    • Lesson 2.2.2: Connecting to data sources
    • Lesson 2.2.3: Importing and using advanced datasets (WEB, API, JSON, ODATA)
  • Chapter 2.3: Managing Power BI Data

    • Lesson 2.3.1: Importing Excel and database files
    • Lesson 2.3.2: Techniques for handling unconventional data
  • Chapter 2.4: Data Shaping and Transformation

    • Lesson 2.4.1: Creating and editing queries
    • Lesson 2.4.2: Combining and reshaping tables
  • Chapter 2.5: Data Modelling in Power BI

    • Lesson 2.5.1: Building relationships and understanding cardinality
    • Lesson 2.5.2: DAX fundamentals: measures and calculations
    • Lesson 2.5.3: Implementing time intelligence
  • Chapter 2.6: Creating Interactive Visualisations

    • Lesson 2.6.1: Designing reports and dashboards
    • Lesson 2.6.2: Using custom visuals, filters, bookmarks, and drilldowns
  • Chapter 2.7: Connectivity and Integration

    • Lesson 2.7.1: Connecting with Cloud Data, SQL Server, Google Analytics
    • Lesson 2.7.2: Integrating with Analysis Services
  • Chapter 2.8: Power BI Web and Mobile

    • Lesson 2.8.1: Power BI mobile app and responsive dashboard design
    • Lesson 2.8.2: Cloud reports, auto-refresh, and natural language queries
Module 3: Python for Data Analysis
  • Chapter 3.1: Python Basics

    • Lesson 3.1.1: Setting up Python and writing basic syntax
    • Lesson 3.1.2: Working with numbers, strings, indexing, and slicing
  • Chapter 3.2: Core Data Structures

    • Lesson 3.2.1: Lists and Tuples
    • Lesson 3.2.2: Dictionaries and Sets
    • Lesson 3.2.3: Boolean operations
  • Chapter 3.3: Programming Fundamentals

    • Lesson 3.3.1: Conditional statements and loops
    • Lesson 3.3.2: List comprehensions and exception handling
  • Chapter 3.4: Working with Modules and Files

    • Lesson 3.4.1: Importing modules and creating packages
    • Lesson 3.4.2: Reading and writing files
  • Chapter 3.5: Functions in Python

    • Lesson 3.5.1: Defining and calling functions
    • Lesson 3.5.2: Using arguments, return values, and lambda functions
  • Chapter 3.6: Object-Oriented Programming

    • Lesson 3.6.1: Classes, objects, attributes, and methods
    • Lesson 3.6.2: Static vs instance methods
  • Chapter 3.7: NumPy for Numerical Computing

    • Lesson 3.7.1: Array creation, indexing, slicing
    • Lesson 3.7.2: Broadcasting and reshaping
    • Lesson 3.7.3: Vectorised operations and random number generation
  • Chapter 3.8: Exploratory Data Analysis with Pandas

    • Lesson 3.8.1: Working with Series and DataFrames
    • Lesson 3.8.2: Data input/output operations
    • Lesson 3.8.3: Cleaning, transforming, and grouping data
  • Chapter 3.9: Data Visualisation with Matplotlib & Seaborn

    • Lesson 3.9.1: Line, bar, and scatter plots
    • Lesson 3.9.2: Box, violin, swarm, and pair plots
    • Lesson 3.9.3: Heatmaps and correlation matrices
  • Chapter 3.10: Statistics for Analysts

    • Lesson 3.10.1: Central tendency and dispersion
    • Lesson 3.10.2: Probability and hypothesis testing
Module 4: MySQL for Data Science
  • Chapter 4.1: Introduction to MySQL

    • Lesson 4.1.1: Installation and configuration
    • Lesson 4.2.1: Connecting to MySQL locally
  • Chapter 4.2: Core SQL Concepts

    • Lesson 4.2.1: SELECT, FROM, WHERE clauses
    • Lesson 4.2.2: Filtering, ORDER BY, and using aliases
    • Lesson 4.2.3: INSERT, UPDATE, DELETE operations
  • Chapter 4.3: Data Aggregation and Manipulation

    • Lesson 4.3.1: Aggregation functions: COUNT, SUM, AVG
    • Lesson 4.3.2: GROUP BY and HAVING clauses
    • Lesson 4.3.3: Subqueries and nested queries
  • Chapter 4.4: SQL Joins and Relationships

    • Lesson 4.4.1: INNER, LEFT, RIGHT, FULL OUTER JOINS
  • Chapter 4.5: Advanced SQL Techniques

    • Lesson 4.5.1: Using window functions
    • Lesson 4.5.2: Common Table Expressions (CTEs)

Download Data Analytics Course Brochure

Real-World Projects in Data Analytics Course in London

Edoxi’s Data Analytics course features hands-on sessions with real-world datasets. This allows you to create live dashboards in Power BI, automate Excel reports, write Python scripts for data analysis, and develop SQL queries in a supportive lab environment. The following are some of the Projects in our Data Analytics Course in London

Projects

  • Sales Performance Dashboard

    Build a comprehensive Power BI dashboard analysing sales trends, regional performance, and product category analysis using real business data.

  • Data Cleaning and Transformation

    Use Python to clean messy datasets, handle missing values, and prepare data for analysis while documenting your process for reproducibility.

  • Automated Excel Reporting System

    Develop an automated reporting solution using Excel formulas, data validation, and macros to streamline regular business reporting needs.

  • Database Query Optimisation

    Write and optimise SQL queries for a relational database to extract meaningful business insights from complex, interconnected data tables.

Data Analytics Course Outcomes and Career Opportunities in London

The Data Analytics course in London provides a solid foundation for your career path in the analytics sector in London, UK. These roles offer excellent growth potential and opportunities across industries, transforming their business processes with data-driven decision making. Here are a few outcomes that you can expect after completing our Data Analytics Course in London;

Course Outcome Image
Understand the fundamental concepts of data analytics and data-driven decision making.
Gain proficiency in using tools like Excel, SQL, Python, R, or Power BI for data analysis.
Learn how to collect, clean, and organise raw data from various sources.
Perform descriptive, diagnostic, predictive, and prescriptive data analyses.
Interpret and visualise data effectively using charts, graphs, and dashboards.
Learn to work with databases and perform data queries using SQL.
Build real-world data projects to strengthen your portfolio.
Prepare for data analyst roles in diverse industries such as finance, healthcare, retail, and tech.

Career Opportunities After the Data Analytics Course in London

  • Data Analyst
  • Reporting Assistant
  • Business Intelligence Associate
  • Business Analyst
  • BI Developer
  • Data Visualisation Specialist
  • Data Manager
  • Analytics Consultant
  • Business Intelligence Manager

Companies Hiring Data Analysts in London, UK

  • Bloomberg
  • Google
  • GSK
  • NatWest Group
  • JPMorganChase
  • J.P. Morgan
  • Legal & General

Data Analytics Training Options

Classroom Training

  • 60-hour instructor-led sessions

  • Practical exercises and real-world projects

  • Small group sessions

  • Comprehensive coverage of concepts

  • Direct interaction with trainers for immediate feedback and clarification

Live Online Training

  • 60-hour online instructor-led sessions

  • Interactive Virtual Classroom Environment

  • Real-Time Instructor Support

  • Collaborative Learning Platforms

  • Session Recordings for Review

  • Study materials

Corporate Training

  • 7-day customised Corporate Training

  • Training delivered at the client’s premises, hotel or Edoxi

  • Customised training and projects

  • Option to choose among the suitable trainers

Do You Want a Customised Training for Data Analytics?

Get expert assistance in getting your Data Analytics Course customised!

How to Get Data Analytics Certified?

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 Training in London?

Here are a few reasons why you should choose Edoxi for Data Analytics Training in London;

Experienced Industry Practitioner

Our trainer brings extensive real-world analytics experience from various industries to the classroom.

Practical Skill Development

Edoxi’s training focuses on hands-on projects using actual business datasets rather than theoretical concepts.

Up-to-date Curriculum

Our course content is continuously updated to align with the current UK market requirements and employer expectations.

Comprehensive Learning Resources

You will receive complete study materials, including templates, notebooks, and datasets for practice beyond class hours.

Extensive Training Locations

Edoxi has offices in Qatar, Dubai and London, and has delivered training in GCC countries and Europe.

Data Analytics Certification

Upon the successful completion of Edoxi’s Data Analytics Course in London, you will receive a course completion certificate from Edoxi.

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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

Lukas Barwicki

Lukas Barwicki is a skilled and versatile Data Analytics, SQL, and Power BI Engineer with excellent leadership and project management capabilities. He is committed to delivering service excellence and value and has a reputation for sophisticated data blending and storytelling. Lukas has several certifications, including CompTIA CySA+, Alteryx Certification, Tableau Data Analyst and Data Scientist, SQL Certification, and Power BI Certification from QA. He completed a BSc in Engineer of Transport & Logistics from the University of Suwalki, Poland, and has six years of experience in Tableau, SQL/T-SQL, and KNIME, five years of experience in Alteryx, three years of experience in Python, and two years of experience in Snowflake.

FAQ

Do I need programming experience to join Edoxi’s Data Analytics Training course in London?
No prior programming experience is required to join our Data Analytics course in London. We start with the basics of each tool and gradually build your skills through practical exercises and guided examples.
How is the online Data Analytics Training conducted?
Our online training uses interactive virtual classrooms with live instruction, screen sharing, and collaborative exercises. You'll have direct access to the instructor for questions.
What are the prerequisites needed to join Edoxi’s Data Analytics Course in London?
Edoxi’s Data Analytics course is ideal for professionals with basic computer skills and familiarity with Excel. While prior experience with data tools is beneficial, it's not mandatory. The training progressively builds skills from foundational concepts to advanced techniques.
Can I use my datasets during the Data Analytics course?
Yes, we encourage you to bring work-related datasets (if not confidential) for specific guidance on applying techniques to your business challenges.
Which is more important to learn first: Excel, Power BI, or Python?
Edoxi’s Data Analytics course is structured to introduce tools in order of complexity, starting with Excel. Each tool builds on skills developed with previous ones, creating a logical learning progression.