Weekdays Only Python training is a LIVE Instructor led training delivered from January 20, 2020 - February 12, 2020 for 16 hours over 4 weeks, 8 sessions, 2 sessions per week, 2 hours per session.
Weekly Schedule
Features and Benefits
The course can be taken by any IT professional having basic knowledge of:
1. Getting Started with Python
Python Overview
About Interpreted Languages
Advantages/Disadvantages of Python pydoc
Starting Python
Interpreter PATH
Using the Interpreter
Running a Python Script
Python Scripts on UNIX/Windows
Python Editors and IDEs.
Using Variables
Keywords
Strings Different Literals
Math Operators and Expressions
Writing to the Screen
String Formatting
Command Line Parameters and Flow Control
Built-in Functions
2. Sequences and File Operations
Lists
Tuples
Indexing and Slicing
Iterating through a Sequence
Functions for all Sequences
Using Enumerate()
Operators and Keywords for Sequences
Dictionaries and Sets
The xrange() function
List Comprehensions
Generator Expressions
3. Deep Dive – Functions Sorting Errors and Exception Handling
Functions
Function Parameters
Global Variables
Variable Scope and Returning Values. Sorting
Alternate Keys
Lambda Functions
Sorting Collections of Collections
Sorting Dictionaries
Sorting Lists in Place
Errors and Exception Handling
Handling Multiple Exceptions
The Standard Exception Hierarchy
Using Modules
The Import Statement
Module Search Path
Package Installation Ways
4. Regular Expressions It’s Packages and Object Oriented Programming in Python
The Sys Module
Interpreter Information
STDIO
Launching External Programs
Paths Directories and Filenames
Walking Directory Trees
Math Function
Random Numbers
Dates and Times
Zipped Archives
Introduction to Python Classes
Defining Classes
Initializers
Instance Methods
Properties
Class Methods and DataStatic Methods
Private Methods and Inheritance
Module Aliases and Regular Expressions.
5. Debugging, Databases and Project Skeletons
Debugging
Dealing with Errors
Using Unit Tests
Project Skeleton
Required Packages
Creating the Skeleton
Project Directory
Final Directory Structure
Testing your Setup
Using the Skeleton
Creating a Database with SQLite 3
CRUD Operations
Creating a Database Object
6. Machine Learning Using Python
Introduction to Machine Learning
Areas of Implementation of Machine Learning
Why Python
Major Classes of Learning Algorithms
Supervised vs Unsupervised Learning
Learning NumPy
Learning Scipy
Basic plotting using Matplotlib
Machine Learning application
7. Supervised and Unsupervised Learning
Classification Problem
Classifying with k-Nearest Neighbours (kNN)
Algorithm
General Approach to kNN
Building the Classifier from Scratch
Testing the Classifier
Measuring the Performance of the Classifier
lustering Problem
8. Scikit and Introduction to Hadoop
Introduction to Scikit-Learn
Inbuilt Algorithms for Use
What is Hadoop and why it is popular
Distributed Computation and Functional Programming
Understanding MapReduce Framework Sample
Map Reduce Job Run
9. Hadoop & Python
PIG and HIVE Basics
Streaming Feature in Hadoop
Map Reduce Job Run using Python
Writing a PIG UDF in Python
Writing a HIVE UDF in Python
Pydoop and MRjob Basics