Machine Learning - CPD Accredited

Course 01: Machine Learning with Python

Course 02: Advanced Diploma in User Experience UI/UX Design

Course 03: Data Science & Machine Learning with R

Course 04: Python Programming for Everybody

Course 05: Data Structures Complete Course

Course 06: Data Science with Python

Course 07: Computer Science: Graph Theory Algorithms

Course 08: Higher Order Functions in Python - Level 03

Course 09: AWS Essentials

Course 10: Cloud Computing / CompTIA Cloud+ (CV0-002)

Course 11: Introduction to Data Analysis

One payment, but lifetime access to 11 CPD courses

Certificate, student ID for the title course included in a one-time fee

Full tutor support available from Monday to Friday

Free up your time - don't waste time and money travelling for classes

Accessible, informative modules taught by expert instructors

Learn at your ease - anytime, from anywhere

Study the course from your computer, tablet or mobile device

CPD accredited course - improve the chance of gaining professional skills

PDF Certificate: Free (Previously it was £10 * 11 = £110)

Hard Copy Certificate: Free (For The Title Course)

Module 01: Introduction to Algorithms

Module 02: Preprocessing

Module 03: Regression

Module 04: Classification

Data Science and Machine Learning Course Intro

Data Types and Structures in R

Data Types and Structures in R

Intermediate R

Data Manipulation in R

Data Visualization in R

Creating Reports with R Markdown

Building Webapps with R Shiny

Introduction to Machine Learning

Starting A Career in Data Science

A Installing Python

Documentation

Command Line

Variables

Simple Python Syntax

Keywords

Import Module

Additional Topics

If Elif Else

Iterable

For

Loops

Execute

Exceptions

Data Types

Number Types

More Number Types

Strings

More Strings

Files

Lists

Dictionaries

Tuples

Sets

Comprehensions

Definitions

Functions

Default Arguments

Doc Strings

Variadic Functions

Factorial

Function Objects

Lambda

Generators

Closures

Classes

Object Initialization

Class Static Members

Classic Inheritance

Data Hiding

UX/UI Course Introduction

Introduction To The Web Industry

Foundations of Graphic Design

UX Design (User Experience Design)

UI Design (User Interface Design)

Optimization

Starting a Career in UX/UI Design

Unit 01: Introduction

Unit 02: Arrays

Unit 03: Liked List

Unit 04: Stack

Unit 05: Queues

Unit 06: Priority Queues (PQs)

Unit 07: Union Find

Unit 08: Binary Search Trees

Unit 09: Fenwick Tree

Unit 10: Hash Tables

Unit 11: Suffix Array

Unit 12: AVL Trees

Unit 13: Indexed Priority Queue

Unit 14: Sparse Tables

Unit 01: Introduction to Python Data Science

Unit 02: Data Cleaning Packages

Unit 03: Data Visualization packages

Module 00: Promo

Module 01: Introduction

Module 02: Common Problem

Module 03: Depth First Search

Module 04: Breadth First Search

Module 05: Breadth First Search Shortest Path on a Grid

Module 06: Trees

Module 07: Topological Sort

Module 08: Dijkstra

Module 09: Bellman-Ford Algorithm

Module 10: Floyd-Warshall Algorithm

Module 11: Bridge and Algorithm Points

Module 12: Tarjan Algorithm

Module 13: Travelling Salesman Problem (TSP)

Module 14: Eulerian Paths and Circuits

Module 15: Prim's Minimum Spanning Tree Algorithm

Module 16: Network Flow

Module 01: Course Introduction

Module 02: Simple Higher Order Functions

Module 03: Sorting with Keys

Module 04: Map Function

Module 05: Filter Function

Module 06: List Comprehension Alternative

Module 07: Recursion Introduction

Section 01: AWS Foundations and Services

Section 02: AWS Security and Costs

Section 01: What You Need to Know

Section 02: Introducing the Cloud

Section 03: System Requirements for Cloud Deployments

Section 04: Cloud Storage

Section 05: Cloud Compute

Section 06: Cloud Networking

Section 07: Cloud Security

Section 08: Migrating to the Cloud

Section 09: Maintaining Cloud Solutions

Section 10: Troubleshooting Cloud Solutions

Module 01: Introduction

Module 02: Agenda and Principles of Process Management

Module 03: The Voice of the Process

Module 04: Working as One Team for Improvement

Module 05: Exercise: The Voice of the Customer

Module 06: Tools for Data Analysis

Module 07: The Pareto Chart

Module 08: The Histogram

Module 09: The Run Chart

Module 10: Exercise: Presenting Performance Data

Module 11: Understanding Variation

Module 12: The Control Chart

Module 13: Control Chart Example

Module 14: Control Chart Special Cases

Module 15: Interpreting the Control Chart

Module 16: Control Chart Exercise

Module 17: Strategies to Deal with Variation

Module 18: Using Data to Drive Improvement

Module 19: A Structure for Performance Measurement

Module 20: Data Analysis Exercise

Module 21: Course Project

Module 22: Test your Understanding