Machine learning : python programming - from beginner to intermediate online course

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Description

  • Type

    Course

  • Methodology

    Online

  • Start date

    Different dates available

Course Description

Python Programming: From Beginner to Intermediate is an essential training course for anyone who wants to begin learning Python. Using a Python IDE (integrated development environment) called iPython from Anaconda, the expert instructors in this course will lead you step-by-step through topics such as: functional language constructs, automated reports, website scraping, and natural language processing.

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Online

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Different dates availableEnrolment now open

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Subjects

  • Database
  • Database training
  • Programming
  • Pyhton
  • Parsing CSV files
  • Download and Unzip
  • Spreadsheets with Python
  • Exception Handling in Python
  • Downloading a webpage
  • Databases from Python

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Online Course Online Course

Online Course Online Course

12 Month Unlimited On-Demand Online Access to the Course.

Course programme

Course Outline

Chapter 01: What is coding? – It’s a lot like cooking!

  • Lesson 01: Introduction
  • Lesson 02: Coding is like Cooking
  • Lesson 03: Anaconda and Pip
  • Lesson 04: Variables are like containers

Chapter 02: Don’t Jump Through Hoops, Use Dictionaries, Lists and Loops

  • Lesson 01: A List is a list
  • Lesson 02: Fun with Lists!
  • Lesson 03: Dictionaries and If-Else
  • Lesson 04: Don’t Jump Through Hoops, Use Loops
  • Lesson 05: Doing stuff with loops
  • Lesson 06: Everything in life is a list – Strings as lists

Chapter 03: Our First Serious Program

  • Lesson 01: Modules are cool for code-reuse
  • Lesson 02: Our first serious program : Downloading a webpage
  • Lesson 03: A few details – Conditionals
  • Lesson 04: A few details – Exception Handling in Python

Chapter 04: Doing Stuff with Files

  • Lesson 01: A File is like a barrel
  • Lesson 02: Auto Generating Spreadsheets with Python
  • Lesson 03: Auto Generating Spreadsheets – Download and Unzip
  • Lesson 04: Auto Generating Spreadsheets – Parsing CSV files
  • Lesson 05: Auto Generating Spreadsheets with XLSXwriter

Chapter 05: Functions are like Food Processors

  • Lesson 01: Functions are like Food processors
  • Lesson 02: Argument Passing in Functions
  • Lesson 03: Writing your first function
  • Lesson 04: Recursion
  • Lesson 05: Recursion in Action

Chapter 06: Databases – Data in rows and columns

  • Lesson 01: How would you implement a Bank ATM?
  • Lesson 02: Things you can do with Databases – I
  • Lesson 03: Things you can do with Databases – II
  • Lesson 04: Interfacing with Databases from Python
  • Lesson 05: SQLite works right out of the box
  • Lesson 06: Manually downloading the zip files required
  • Lesson 07: Build a database of Stock Movements – I
  • Lesson 08: Build a database of Stock Movements – II
  • Lesson 09: Build a database of Stock Movements – III

Chapter 07: An Object Oriented State of Mind

  • Lesson 01: Objects are like puppies!
  • Lesson 02: A class is a type of variable
  • Lesson 03: An Interface drives behaviour

Chapter 08: Natural Language Processing and Python

  • Lesson 01: Natural Language Processing with NLTK
  • Lesson 02: Natural Language Processing with NLTK – See it in action
  • Lesson 03: Web Scraping with BeautifulSoup
  • Lesson 04: A Serious NLP Application : Text Auto Summarization using Python
  • Lesson 05: Auto Summarize News Articles – I
  • Lesson 06: Auto Summarize News Articles – II
  • Lesson 07: Auto Summarize News Articles – III

Chapter 09: Machine Learning and Python

  • Lesson 01: Machine Learning – Jump on the Bandwagon
  • Lesson 02: Plunging In – Machine Learning Approaches to Spam Detection
  • Lesson 03: Spam Detection with Machine Learning Continued
  • Lesson 04: News Article Classification using K-Nearest Neighbors
  • Lesson 05: News Article Classification using Naive Bayes
  • Lesson 06: Code Along – Scraping News Websites
  • Lesson 07: Code Along – Feature Extraction from News articles
  • Lesson 08: Code Along – Classification with K-Nearest Neighbours
  • Lesson 09: Code Along – Classification with Naive Bayes
  • Lesson 10: Document Distance using TF-IDF
  • Lesson 11: News Article Clustering with K-Means and TF-IDF
  • Lesson 12: Code Along – Clustering with K-Means


PACKAGE INCLUDES:

Length of Subscription: 12 Months Online On-Demand Access
Running Time: 10 hrs 30 min
Platform: Windows & MAC OS
Level: Beginner to Advanced
Project Files: Included

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Machine learning : python programming - from beginner to intermediate online course

Price on request