Weekdays Only Python Training in Hong Kong | Introduction to Python for beginners | What is Python? Why Python? Python Training | Python programming training | Learn python | Getting started with Python programming |January 13, 2020 - January 29, 2020

TruVs Inc, is a modern business and technology consulting company. We help our customers modernize their business operations using world class business processes and cutting edge technologies. We have deep expertise in the areas of focus. Our customers are typically fortune 500 enterprises having global presence. We are head quartered in Seattle Metro area in USA but operate globally. We have been profitable since we were founded in 2011.

TruVs

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.
<UL>
<LI>All Published Ticket Prices are in US Dollars</LI>
<LI>The course will be taught in English language only.</LI>
</UL>
 
<H6>Weekly Schedule</H6>
<UL>
<LI>4 Weeks | Monday, Wednesday Every Week</LI>
<LI>5:30 PM - 7:30 PM US Pacific time each day</LI>
<LI>January 20 - February 12, 2020 US Pacific time</LI>
</UL>
<A HREF="https://www.timeanddate.com/worldclock/converter.html?iso=20200121T013000&p1=234" TARGET="_blank" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">Please check your local date and time for first session</A>
 
<H6>Features and Benefits</H6>
<UL>
<LI>4 weeks, 8 sessions, 16 hours of total Instructor-led LIVE training</LI>
<LI>Training material, instructor handouts and access to useful resources on the cloud provided</LI>
<LI>Practical Hands-on Lab exercises provided</LI>
<LI>Actual code and scripts provided</LI>
<LI>Real-life Scenarios</LI>
</UL>
 
<H6> </H6>
<H6>Course Objectives</H6>
<UL>
<LI>Complete knowledge of Python</LI>
<LI>Learn how to use lists, tuples, loops, decision statement, etc. in python</LI>
<LI>Build packages in Python</LI>
<LI>Working with Exception handling, Inheritance</LI>
<LI>Work independently in Project with scripting and Automation</LI>
</UL>
 
<H6> </H6>
<H6>What are the prerequisites to learn Python?  </H6>
The course can be taken by any IT professional having basic knowledge of:
<UL>
<LI>Unix or Windows Operating System</LI>
<LI>Any Programming Language</LI>
<LI>Computer concepts</LI>
</UL>
 
<H6> </H6>
<H6>Who can take Python Course?</H6>
<UL>
<LI>Any Professional who is interested in building career in python web development/ software automation /Data Analytics.</LI>
<LI>Any one who wants to learn python programming for any purpose</LI>
</UL>
 
<H6> </H6>
<H6>Python Online Training Course Curriculum</H6>
1. Getting Started with Python
<UL>
<LI>
Python Overview
</LI>
<LI>
About Interpreted Languages
</LI>
<LI>
Advantages/Disadvantages of Python pydoc
</LI>
<LI>
Starting Python
</LI>
<LI>
Interpreter PATH
</LI>
<LI>
Using the Interpreter
</LI>
<LI>
Running a Python Script
</LI>
<LI>
Python Scripts on UNIX/Windows
</LI>
<LI>
Python Editors and IDEs.
</LI>
<LI>
Using Variables
</LI>
<LI>
Keywords
</LI>
<LI>
Strings Different Literals
</LI>
<LI>
Math Operators and Expressions
</LI>
<LI>
Writing to the Screen
</LI>
<LI>
String Formatting
</LI>
<LI>
Command Line Parameters and Flow Control
</LI>
<LI>
Built-in Functions
</LI>
</UL>
 
2. Sequences and File Operations
<UL>
<LI>
Lists
</LI>
<LI>
Tuples
</LI>
<LI>
Indexing and Slicing
</LI>
<LI>
Iterating through a Sequence
</LI>
<LI>
Functions for all Sequences
</LI>
<LI>
Using Enumerate()
</LI>
<LI>
Operators and Keywords for Sequences
</LI>
<LI>
Dictionaries and Sets
</LI>
<LI>
The xrange() function
</LI>
<LI>
List Comprehensions
</LI>
<LI>
Generator Expressions
</LI>
</UL>
 
3. Deep Dive – Functions Sorting Errors and Exception Handling
<UL>
<LI>
Functions
</LI>
<LI>
Function Parameters
</LI>
<LI>
Global Variables
</LI>
<LI>
Variable Scope and Returning Values. Sorting
</LI>
<LI>
Alternate Keys
</LI>
<LI>
Lambda Functions
</LI>
<LI>
Sorting Collections of Collections
</LI>
<LI>
Sorting Dictionaries
</LI>
<LI>
Sorting Lists in Place
</LI>
<LI>
Errors and Exception Handling
</LI>
<LI>
Handling Multiple Exceptions
</LI>
<LI>
The Standard Exception Hierarchy
</LI>
<LI>
Using Modules
</LI>
<LI>
The Import Statement
</LI>
<LI>
Module Search Path
</LI>
<LI>
Package Installation Ways
</LI>
</UL>
 
4. Regular Expressions It’s  Packages and Object Oriented Programming in Python
<UL>
<LI>
The Sys Module
</LI>
<LI>
Interpreter Information
</LI>
<LI>
STDIO
</LI>
<LI>
Launching External Programs
</LI>
<LI>
Paths Directories and Filenames
</LI>
<LI>
Walking Directory Trees
</LI>
<LI>
Math Function
</LI>
<LI>
Random Numbers
</LI>
<LI>
Dates and Times
</LI>
<LI>
Zipped Archives
</LI>
<LI>
Introduction to Python Classes
</LI>
<LI>
Defining Classes
</LI>
<LI>
Initializers
</LI>
<LI>
Instance Methods
</LI>
<LI>
Properties
</LI>
<LI>
Class Methods and DataStatic Methods
</LI>
<LI>
Private Methods and Inheritance
</LI>
<LI>
Module Aliases and Regular Expressions.
</LI>
</UL>
 
5. Debugging, Databases and Project Skeletons
<UL>
<LI>
Debugging
</LI>
<LI>
Dealing with Errors
</LI>
<LI>
Using Unit Tests
</LI>
<LI>
Project Skeleton
</LI>
<LI>
Required Packages
</LI>
<LI>
Creating the Skeleton
</LI>
<LI>
Project Directory
</LI>
<LI>
Final Directory Structure
</LI>
<LI>
Testing your Setup
</LI>
<LI>
Using the Skeleton
</LI>
<LI>
Creating a Database with SQLite 3
</LI>
<LI>
CRUD Operations
</LI>
<LI>
Creating a Database Object
</LI>
</UL>
 
6. Machine Learning Using Python 
<UL>
<LI>
Introduction to Machine Learning
</LI>
<LI>
Areas of Implementation of Machine Learning
</LI>
<LI>
Why Python
</LI>
<LI>
Major Classes of Learning Algorithms
</LI>
<LI>
Supervised vs Unsupervised Learning
</LI>
<LI>
Learning NumPy
</LI>
<LI>
Learning Scipy
</LI>
<LI>
Basic plotting using Matplotlib
</LI>
<LI>
Machine Learning application
</LI>
</UL>
 
7. Supervised and Unsupervised Learning 
<UL>
<LI>
Classification Problem
</LI>
<LI>
Classifying with k-Nearest Neighbours (kNN)
</LI>
<LI>
Algorithm
</LI>
<LI>
General Approach to kNN
</LI>
<LI>
Building the Classifier from Scratch
</LI>
<LI>
Testing the Classifier
</LI>
<LI>
Measuring the Performance of the Classifier
</LI>
<LI>
lustering Problem
</LI>
</UL>
 
8. Scikit and Introduction to Hadoop
<UL>
<LI>
Introduction to Scikit-Learn
</LI>
<LI>
Inbuilt Algorithms for Use
</LI>
<LI>
What is Hadoop and why it is popular
</LI>
<LI>
Distributed Computation and Functional Programming
</LI>
<LI>
Understanding MapReduce Framework Sample
</LI>
<LI>
Map Reduce Job Run
</LI>
</UL>
 
9. Hadoop & Python
<UL>
<LI>
PIG and HIVE Basics
</LI>
<LI>
Streaming Feature in Hadoop
</LI>
<LI>
Map Reduce Job Run using Python
</LI>
<LI>
Writing a PIG UDF in Python
</LI>
<LI>
Writing a HIVE UDF in Python
</LI>
<LI>
Pydoop and MRjob Basics
</LI>
</UL>

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Weekdays Only Python Training in Hong Kong | Introduction to Python for beginners | What is Python? Why Python? Python Training | Python programming training | Learn python | Getting started with Python programming |January 13, 2020 - January 29, 2020

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Weekdays Only Python Training in Hong Kong | Introduction to Python for beginners | What is Python? Why Python? Python Training | Python programming training | Learn python | Getting started with Python programming |January 13, 2020 - January 29, 2020

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