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Data Analysis with Python

A Beginner level 12-hour course delivered via Instructor-led Physical Classes or Virtual Classes.

Regular Price: £420
Batch Price: From £360   📅  View Dates & Prices

Group Booking Discount: From £240 per person  🧮 Calculate & Book

1-to-1 Training: £420  📋 Booking Request Form
Data Analysis with Python Trainign Course

Course Overview

Python is a multi-paradigm programming language which has become the language of choice for data analysis, data visualisation and machine learning. This Data Analysis with Python course provides a concrete first step in learning data analysis.

In this course, you will be working with Jupyter notebook and setting up a database. After covering the Jupyter, you will learn Python’s NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and functions. Later you will explore Python’s pandas extension for data mining, managing your datasets by sorting and ranking them. Last but not least you’ll learn data visualisation with matplotlib.


Requirements

This course is suitable for those who already have basic knowledge of Python programming.

We highly recommend you complete the following course(s) before attending the Data Analysis with Python course:


Course Content

  1. Introduction to Data Analysis
    • What is data analysis
    • Why data analysis
    • Types of data analysis
    • Process flow of data analysis
  2. Introduction to NumPy
    • Pandas & NumPy Intro
    • Numpy Arrays & Array Properties
    • Array Creation
    • Random Number Generation
    • Indexing & Slicing Arrays
    • Array Operations
  3. Introduction to Pandas
    • Defining pandas library
    • Why do we need pandas library
    • Pandas data structure
    • Exploring the data of a DataFrame
    • Selecting data from DataFrame
    • Data cleaning in pandas DataFrame
    • Grouping and aggregation
    • Sorting and ranking
    • Adding row into DataFrame
    • Adding column into DataFrame
    • Dropping the row/column from DataFrame
    • Concatenating the dataframe
    • Merging/joining the dataframe
    • The merge() function
    • The join() function
    • Writing the DataFrame to external files.
  4. Data Visualisation with Matplotlib
    • What is data visualisation
    • What is Matplotlib
    • Getting started with Matplotlib
    • Line plot using Matplotlib
    • Customising the plot
    • Some basic types of plots in matplotlib
    • Export the plot into a file


Course Dates, Prices & Enrolment

Scroll right for more details
Delivery MethodDates & TimesHoursPriceEnrolment
Online Training using Zoom
04 Jan 2026 - 11 Jan 2026
2 Sundays
10:00 AM - 04:00 PM BT
12-hour over 2-day
£360 £420
Enrol Now
Online Training using Zoom
19 Jan 2026 - 30 Jan 2026
Mon, Wed & Fri (2 wks)
03:00 PM - 05:00 PM BT
12-hour over 6-day
£360 £420
Enrol Now
Online Training using Zoom
31 Jan 2026 - 14 Feb 2026
3 Saturdays
10:00 AM - 02:00 PM BT
12-hour over 3-day
£360 £420
Enrol Now
Online Training using Zoom
16 Feb 2026 - 27 Feb 2026
Mon, Wed & Fri (2 wks)
03:00 PM - 05:00 PM BT
12-hour over 6-day
£360 £420
Enrol Now
Online Training using Zoom
14 Mar 2026 - 28 Mar 2026
3 Saturdays
10:00 AM - 02:00 PM BT
12-hour over 3-day
£360 £420
Enrol Now
Online Training using Zoom
16 Mar 2026 - 27 Mar 2026
Mon, Wed & Fri (2 wks)
03:00 PM - 05:00 PM BT
12-hour over 6-day
£360 £420
Enrol Now
Note: Online classes are usually delivered through Zoom video conferencing.

Price Calculator & Booking Request Form

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Participant Reviews

“Well taught, with good materials.”

Philip, 17 April 2025

“The trainer was friendly, helpful and knowledgeable. Would recommend this course.”

Louis, 16 August 2024

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What we do?

At London Academy of IT, we provide instructor-led online and in-person IT training in Data Analytics, SQL, Python, Power BI, and more. Our cutting-edge courses are designed to boost performance and enhance employability, providing the competitive edge employers look for.

Our Contacts

London Academy of IT
64 Broadway
Stratford
London E15 1NT
United Kingdom

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