what is Python?
General purpose programming language can be used for variety of tools, utility, aapplication development
Why Python?
Can be used in varied application development
Can be used XML and Natural langugae Processing
Networking and Services
GUI applications
Data Anytics and Big data processing etc
Benefits of using Python::
Simple and easy to learn
General purpose language used for any software development activities
Plethora of users and large community
Python is versatile in features and less programming codes
Plenty of Support Libraries
Integration with varity of applications
Non Benefits of python:
Mostly used for analytics , data capturing and data collection applications
May not be widely used for web applications where other programming languages dominates
Not a enterprise and mobile applications choice
For those that needs to understand python programming and implementation
internet developers, Technical leads and others
For those who work on product or service.
For those that needs to become professional in python internet development.
For managers or ends up in manage comes or for hiring.
to use application development techniques to a personnal project.
Applications and Frameworks
Get Started with programming
Variables and Data Types
Operators and Expressions
Control Structure
Sequence Types,Dictionaries and Sets
List Comprehensions
Functions, Local, Non Local & Global Variables
Anonymous and Lambda Functions
Files and Exception Handling
Date, Time and Calendar API
Command Line Frameworks
Regular Expressions and Parsing
Graphics and GUI
OOPS Concepts,Classes and Objects
Super class and User Defined Classes
Default Attributes and Methods
Function and Operator Overloading
Inheritance and Multiple Inheritance
Function Overriding and Polymorphism
class method and Static method
Descriptors and Interceptors
Properties and Attribute Access
Iterators, Generators and Decorators
Streams & Context Manager
Database Programming
Sockets and Networking
Logging and Debugging
Modules and Packages
Distributing Applications
Unit and Integration Testing
Documentation and Best Practices
Project, Assignments and Tests
Python Application Development expertise
Project Implementation and hands on concepts
Python coaching Material and program Samples
In depth core python programming coaching
Training are going to be conducted by subject material professional in software package Development, product and Technology coaching.
The syllabus includes planned sessions with displays, sensible exercises and hands on project implementation.
Introduction, Applications and Frameworks, Get Started with programming, Variables and Data Types, Operators and Expressions , Control Structure, Sequence Types, Dictionaries and Sets , List Comprehensions, Functions, Local, Non Local & Global Variables, Anonymous and Lambda Functions
Environment Set Up , Anaconda, IPython Shell, IPython Notebooks, Pycharm, Spyder IDE, Run Python scripts, Loading packages, namespaces
Numerical Analysis using NumPy, Introduction to NumPy, NumPy overview , Creating NumPy arrays , Doing math with arrays , Indexing and slicing , Records and dates , Downloading and parsing data files , Using Scipy
Accessing and Preparing Data, Acquiring Data with Python, Loading from CSV files, Accessing SQL databases, Cleansing Data with Python, Stripping out extraneous information, Normalizing data, Formatting data, Debugging, Code profiling
Data manipulation with Pandas, Pandas overview , DataFrames in pandas , Using multilevel indices, Series in pandas , Statistical analysis , Grouping, aggregating and applying, scipy.stats , Tabular Data Analysis with Pandas , Data Munging in Python using Pandas
Advanced Analytics, SciPy and Scikit , Data Modelling , Machine Learning with scikit-learn, Estimator, predictor, transformer interfaces, Pre-processing data , Building a Predictive Model , Regression , Classification , Model selection , Logistic Regression , Decision Tree, Random Forest
Visualization Tools , Overview , Mathplotlib , Numpy , Seaborn , Input: 2D, samples, and features , statistical graphics , Data Reporting , Extract datasets for specific reports (routine and adhoc) , Prepare reports on observed trends and patterns( Daily/weekly/monthly & quarterly , Develop graphs, reports, and presentations based on observation., Create management dashboards based on derived data collections.
Web Scrapping & NLK , NLK, Scrapy.py, urllib , Pylib , Beautiful soup
Project