Python Bootcamp UK

Python Boot Camp, 12-week

Learn Python, Ideal for Data Analysts and Aspiring Python Developers.

With this comprehensive online, instructor-led Python Bootcamp, you will develop practical, job-ready Python programming skills through structured lessons, hands-on coding, expert guidance and real-world projects.

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1-1 Python Mentoring

1-1 Python Mentoring

Additional support, between sessions.
Work at your pace, 1-1 sessions can cover additional Python exercises, practical work and help you catch up with the course.
Build confidence, because we review and validate your practical Python work.
Get direct support, with immediate answers to your Python programming questions.

Python Self-Study

Python Self-Study

Learn by doing, practical self-study helps reinforce Python programming concepts through independent coding.
Practical, most self-study work consists of Python exercises and programming tasks.
Gain experience, this part of the Python Bootcamp gives you additional opportunities to practise skills relevant to professional programming work.

Python Practical Project

Python Practical Project

Live online project work, develop and upload your Python project.
Showcase your skills, demonstrate your Python programming experience through practical project work.
Build your portfolio, your project can be uploaded to GitHub and shared as evidence of your Python development skills.

Python Bootcamp Materials

Python Bootcamp Materials

Python Coding Examples, plenty of practical Python programming examples to support learning.
Manuals and notes providing useful Python reference materials.
Exercises, practical Python coding exercises with every class.

Python Bootcamp Payments

Python Bootcamp Payment Options

Check the booking link for available Options
Installments, 2 for 1 offers and discounts may be available; check the booking link for current options.

Our Python Bootcamp Training Style

Our Python Bootcamp Training Style

Personalised, 1-1 Python mentoring and small groups, maximum 4 learners.
Practical, Hands-on. Learn Python through coding exercises, projects and guided practice.
Online Instructor-Led Python Bootcamp training.

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Python Boot Camp Topics and Course Details

Python Boot Camp lesson topic descriptions

Introduction to Python programming and core Python fundamentals:
Python data types and variables:
Primitive data types; Characters; Boolean values; Working with variables and variable scope; Type conversion and type casting.
Python strings and text processing
String functions and working with strings, numbers and dates.
Getting user input and processing input data.
Python operators and expressions:
Introduction to operators; Arithmetic operators; Relational operators; Assignment operators; Logical operators; Increment and decrement operations.
Python decision making:
If statements; If-else statements; If-elif-else statements; Nested if-else statements; Conditional logic.
Python loops and iteration:
The while and for loops; Enhanced iteration techniques; Jump statements including break and continue; The return statement; Nested loops.

Python object-oriented programming principles
Using Python Methods:
Learn Python method fundamentals, including defining methods, parameters, return values, method overloading, calling methods and encapsulation.
Python Classes and Objects
Inheritance, method overriding, constructors, parameterised constructors, the self keyword and inner classes.
Practical Python Project
Create a movie booking system using Python objects for different movie locations.

UX principles and user interface design
Applying UX principles to Python front-ends with Tkinter.
Create a practical movie booking front-end using Python and Tkinter.

Connect Python applications to a SQLite3 database.
Working with dates and date-related data.
Python localisation and internationalisation concepts.
Python strings and string processing.
Mathematical operations in Python.
Generating random numbers with Python.
Python lambda functions and functional programming techniques.

Python lists, tuples, sets and dictionaries; Working with JSON files.
Using Python built-in modules and functions for strings, mathematics and dates.
Exception handling, files and streams in Python.

Database concepts and relational databases
SQL data types, columns and tables.
Database relationships and relational data modelling.
SQL statements and database queries.
DDL SQL statements.
Creating and dropping databases.
Creating, altering and dropping database tables.
SQL SELECT queries: WHERE clauses, wildcards, ORDER BY, JOINs, aggregate functions and HAVING clauses.
DML queries: INSERT, UPDATE and DELETE records.
Connect Python applications to a SQLite3 database.
Data-driven Python project development.
DDL queries: Create tables, alter tables and drop tables.
Creating transaction logs using Python and SQL.
DML queries: Insert, delete and update records.
Creating a Python login facility to register, delete and maintain users.
Create a database search facility using SQL SELECT queries.
Query a database using wildcard parameters and display search results.
Practical project: Create a movie list by location and a customer login database.

Python NumPy arrays: Working with arrays, creating data using arrays, array manipulation and array-wise mathematical functions. Working with strings in NumPy arrays.
NumPy built-in functions: Mathematical, arithmetic and statistical functions.
NumPy calculations and numerical data processing.

Python Pandas Series.
Data cleaning and preparation.
Python Pandas DataFrames and data importing.
Python DataFrames.
Data Series, date/time functionality and time series.
Creating DataFrames and indexing.
Dictionary to DataFrame and DataFrame to dictionary.
CSV to DataFrame and DataFrame to CSV.
Excel to DataFrame and DataFrame to Excel.
Data cleaning and preparation.
Finding, replacing and filtering missing data.
Removing duplicates.
Replacing values.
Renaming axis indexes.
Python Pandas data wrangling.
Discretisation and binning.
Random sampling.
Transforming data using functions and mapping.
Hierarchical indexing.
Reordering and sorting data.
Statistics and DataFrame analysis.
DataFrame joins, merging, concatenation and overlap.
Reshaping and pivoting data.
Querying a Pandas DataFrame.
Python data analysis:
Sorting data.
Analysing and finding data using filters, slicing and DataFrame queries.
Finding data through iteration.
Finding statistics using functions and aggregate functions.
Working with unique values.
String objects and regular expressions (Regex).

Python chart types: Bar, Column, Line, Scatter, Pie, Area, Histogram and Funnel charts.
Chart formatting: Changing gridlines, lines, axes, scales, markers and colours.
Chart elements: Legends, titles, plot sizes and exporting charts.

Supervised machine learning using Python.
Classification algorithms:
Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors and Support Vector Machine.
Regression algorithms: Linear Regression and Polynomial Regression.

Unsupervised machine learning using Python.
Clustering algorithms: K-means clustering and hierarchical clustering.
Dimension reduction algorithms: Principal Component Analysis (PCA) and Latent Dirichlet Allocation (LDA).
Association algorithms: Apriori and Eclat.
Ensemble machine learning methods: Stacking, bagging and boosting. Random Forest and Gradient Boosting.
Neural networks and deep learning algorithms: Convolutional Neural Networks (CNN).
Data exploration and preprocessing.
Python data preprocessing techniques covering data cleaning, data transformation and preparation to support effective data exploration and analysis.

Python Front-End Development with Tkinter and Web Technologies

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Python bootcamp free trial

Python bootcamp free trial