python Bootcamp uk
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Python Boot Camp, 8-weeks

Details - Weekly topics - Book the course
PYTHON CODING BOOT CAMP LONDON, UK, 8-WEEKS BLENDED LEARNING PROGRAM, £2100
Python Course details

Python Boot Camp, 8-weeks

Learn to Python, Ideal for Data Analysts.


With this excellent Python Programming course London you will achieve job-ready coding expertees.

    How does it work?
  • Online, Instructor-led lessons: 1 full day lesson per week, for 8 weeks
  • Plus Self-study Materials and a Structured Self-Study Program
  • Plus 1-1 mentoring Scheduled in addition
  • Plus Live Online Practical Project to showcase your expertees

Part Time

Part Time
  • 1 full day per week, online instructor-led.
    Self study, in your own time.
    1-1 mentoring, schedule your preferred time.
    Earn and Learn, stay employed, work, earn your salary until you qualify, then change.

1-1 Mentoring

1-1 Mentoring
  • Additional, between weekly sessions.
    Work at your pace, 1-1 sessions can cover extra work and/or help you catch up.
    Gain confidence, because we revise & validate your practicals.
    Be re-assured, get immediate answers to your questions.

Self-Study

Self-Study
  • Learn by doing, the best way to re-inforce learning, is by trying on your own.
    Practical, most of the self-study work is practical exercises.
    Gain experience, this aspect of the course gives you experience employesr are seeking.

Practical Project

Practical Project
  • Live online, upload your project.
    Showcase, your expertees are testified online.
    Become known, your project will put you in contact with the coding community.

Materials

Materials

  • Python Coding Examples, Plenty thereof.
    Manuals and Notes Reference materials.
    Exercises, Practical work with every class.

Payments

Payments
  • Best deal: Best deal
    Installments: Contact us to arrange.

Our Style

Our Style
  • Personalised, 1-1 Mentoring & Small Groups, Max 4.
    Practical, Hand-on.
    Online Instructor-Led.
Weekly topics and other details
Weekly Python lesson topic descriptions


  • Overview of Python Fundamentals:
  • Python Data Types, Variables:
  • Primitive types; Characters; Boolean; Working with variables and its scope; Type conversion and casting;
  • Strings
  • String Functions, Strings vs numbers vs dates.
  • Getting user input.
  • Python Operators and Expressions:
  • Introduction of operators; Arithmetic operators; Relational operators; Assignment operator; Logical operators; Increment and decrement operators.
  • Decision Making:
  • If statement; If - else statement; If- else if - else statement; Nested if - else; Switch Statements
  • Using Loops:
  • The while, do-while and the for loop; Enhanced for loop; Jump statements : break, continue; The return statement; Nesting loops.

  • OOP Principals
  • Using Methods:
    Learn Python method basics. Defining Methods, Parameters, Returning values, Overloading methods, Calling methods. Encapsulation.
  • Classes and Objects Inheritance, Override, Constructors, Parametised Constructors, the self keyword, Inner classes

  • Lists. Tuples. Sets, Dictionary. Json Files.
  • Using Built-in modules and functions for strings, maths and dates.
  • Exception Handling, Files, Streams.

  • Database concepts, Relational Database
  • Data Types, Columns, Tables
  • Relationships
  • SQL statements
  • DDL SQL Statements:
  • Create and drop a databases
  • Create,aleter and drop alter tables
  • Select queries: where-clauses, wildcards, order by, joins, aggregates, having,
  • DML Queries: Insert, Update and deleting records

  • Connect to a from Python to a SQLite3 database,
  • Data Driven Python Project:
  • DDL Queries: Create a table, alter tables, drop a table
  • Creating a log of transactions, using the above
  • DML Queries: insert, delete, update records
  • Creating a log-in facility to register, delete and maintain users
  • Create a Search facility using select queries
  • Query a database with wildcard parameters and display results

  • Numpy Arrays The Python NumPy Module: Working with arrays, create data using arrays. Array manipulation and array-wise math functions. String functions on arrays.
  • Numpy Built-In Functions : Math, arithmetic and statistical functions.
  • Numpy Calculations

  • Pandas Series
  • Data Cleaning
  • Python Pandas Dataframes and data importing
    Python Dataframes
    Data Series. Date/ Time Functionality. Time series.
  • Creating Dataframes, Indexing.
    Dict to Dataframe, Dataframe to Dict.
    Csv to Dataframe, Dataframe to csv.
    Excel to Dataframe, Dataframe to Excel.
  • Data Cleaning and preparation
    Finding, replacing and filtering missing data.
    Remove Duplicates.
    Replacing values.
    Renaming Axis Indexes.
  • Pandas Data Wrangling
    Discretization and Binning.
    Random Sampling.
    Transforing data using function and mapping,
    Hierarchical Indexing,
    Reorder,
    Sorting, Stastitics,
    Dataframe Joins, Merging, Concatenation, Overlap.
    Reshaping and pivoting.

  • Query a Pandas Dataframe
  • Data Analysis:
    Sorting.
    Analysing and finding data using filter, slicing and dataframe queries.
    Finding data by Iteration.
    Find statistics: Functions, Aggregate functions.
    Unique values.
    String objects, Regex.

  • Chart Types: Bar, Column, Line, Scatter, Pie, Area, Histogram, Funnel Charts
  • Formatting: Changing gridlines lines, axes, scales, markers, colours,
  • Chart Elements: legends, titles, plot seizes, exporting.

  • Supervised Machine Learning:
  • Classification Algorithms:
    • Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine
  • Regression Algorithms: Linear, Polynomial

  • Unsupervised Machine Learning:
  • Clustering Algorithms: K-means clustering, Hierarchical Clustering
  • Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA)
  • Association Algorithms: Apriori, Euclat
  • Ensemble Methods Algorithms: Stacking, bagging, boosting. Random Forest Random Forest, Gradient Boosting
  • Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN)
  • Data Exploration and Preprocessing:
  • Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy.

  • Python Tkinter Front-end Basics
  • Getting Started with HTML
  • Getting Started with CSS
  • Getting Started with Php
  • Getting Started with JavaScripts

Book the Python Boot Camp


About us
Our experienced trainers are award winners.
Awards

  • Sarah Barnard wins industry recognition as Freelance Trainer of the Year UK02 Feb 2007Learning NewsBray Leino Learning

    Sarah Barnard was judged to be the Freelance Trainer of the Year at the Institute of IT Training's awards dinner last night. The title is bestowed on the individual who has shown exceptional skills in managing, delivering, and/or contributing, through training assignments, to the success of their clients over the past twelve months. BroadSkill, the UK's largest supplier of freelance trainers and performance solutions sponsor the award.
    In selecting the winner, the judges particularly liked the innovative use of automation behind Sarah's regular newsletter and focus she always maintains on establishing value for her clients.

    This is the third year for the award which was put in place to recognise excellence amongst the growing ranks of independent trainers. The majority of training delivery in the UK is delivered by independent trainers and they support businesses and their people to perform day in and day out often with little recognition. Throughout the last 5 years we have witnessed a massive shift away from permanent employment of trainers and independent trainers are now estimated to make at least 70% of the UK delivery workforce, according to BroadSkill. Such trainers need not only to be able stand up in front of a class delivering in depth knowledge and learning but also have to carry out training needs analysis, provide learning consultancy, develop courses and manage projects, as well as selling their own services and managing their own businesses.

    This year was a very tight final with two excellent candidates. The Institute awarded the Silver award to Julia Emelogu, last year's winner.
    Sarah Barnard has developed a unique approach with her Time Saver Training™ which delivers learning that is tightly focussed on increasing productivity in the workplace. The basis of her approach is that once staff have a better understanding of their software, they are then able to use it more productively. This in turn leads to increased productivity for the employee and increased productivity for the company.

    The judges were impressed with Sarah's excellent understanding of adult learning principles and the rigorous testing strategy that she uses to measure and evaluate the training intervention.

    Henry Jodrell, Sales and Marketing Director at BroadSkill, who presented the award, said: "we send our heartiest congratulations to Sarah for this well-deserved award. Being a successful freelance trainer takes a lot of skill and dedication and at BroadSkill we are committed to recognising success whenever and wherever we can. Winners of this award provide role models and help us in developing the profession, both within our own associate trainer base and in our quest to bring new instructors into the industry."


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