Python Programming: From Beginner to Intermediate Online Course
Learning 247
Summary
- Certificate of completion - Free
Overview
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.
Description
What am I going to get from this course?
- Pick up programming even if you have NO programming experience at all
- Write Python programs of moderate complexity
- Perform complicated text processing – splitting articles into sentences and words and doing things with them
- Work with files, including creating Excel spreadsheets and working with zip files
- Apply simple machine learning and natural language processing concepts such as classification, clustering and summarization
- Understand Object-Oriented Programming in a Python context
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
Learn anytime, anywhere, at home or on the go.
Stream your training via the internet, or download to your computer and supported mobile device, including iPad, iPhone, iPod Touch and most Android devices.
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
Who is this course for?
What is the target audience?
- Folks with zero programming experience looking to learn a new skill
- Machine Learning and Language Processing folks looking to apply concepts in a full-fledged programming language
- Computer Science students or software engineers with no experience in Java, but experience in Python, C++ or even C#. You might need to skip over some bits, but in general the class will still have new learning to offer you.
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Certificates
Certificate of completion
Digital certificate - Included
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This course is advertised on reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.
