Data science using python

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About Course

Gain the career-building Python skills you need to succeed as a data scientist. No prior coding experience required. In this track, you’ll learn how this versatile language allows you to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional or researcher. Through interactive exercises, you’ll get hands-on with some of the most popular Python libraries, including pandas, NumPy, Matplotlib, and many more.

What Will You Learn?

  • Python Programming is intended for software engineers, data analysts, data scientists, machine learning engineers, program managers and user support personnel who wish to learn the Python programming language.
  • Data Cleaning Project
  • Data Visualization Project

Course Content

Introduction to python
To understand why Python is a useful language for developers. Receive an overview of what you’ll be learning and doing in the course which involves in learning following topics: Why to Learn Python?,Characteristics of Python,Applications of Python,Installation of Python,Local Environment Setup.

Language Fundamentals
To define the structure and components of a Python program and to learn how to design and program Python applications involves Basic Syntax and represent data using Python's data types: integers, floats, booleans, strings, lists, tuples, sets, dictionaries, compound data structures. Perform computations and create logical statements using Python’s operators: Arithmetic, Assignment, Comparison, Logical, Membership, Identity

Control Statements
To learn how to write loops and decision statements in Python. Write conditional expressions using if statements and boolean expressions to add decision making to your Python programs Use for and while loops along with useful built-in functions to iterate over and manipulate lists, sets, and dictionaries

Strings
To know how to Create string in python, Strings indexing and splitting,Reassigning Strings,Deleting the String ,String operator,Python string Formatting,Python string Methods

Python containers
To learn how to use List data structure, Tuple data structure, Set data structure, Dictionary data structure

Indexing and Slicing
To learn how to use indexing and slicing to access data in Python programs. syntax: sequence[start:stop] and sequence[start:stop:step].

Functions
To learn how to write functions and pass arguments in Python. Functions can be both built-in or user-defined. It helps the program to be concise, non-repetitive and organized. Define your own custom functions, Create and reference variables using the appropriate scope.

Exception Handling
To learn how to use exception handling in Python applications for error handling

File Handling
how to read and write files in Python

Regular Expressions

Modules and packages
To learn how to build and package Python modules for reusability

Object‐oriented programs
To learn how to design object‐oriented programs with Creating Classes and Objects, Abstraction, Encapsulation and Inheritance.To learn how to use class inheritance in Python for reusability.

Database
Database Programming and Database connection in python

Python Libraries for Data Analysis

Numpy

Pandas

Scipy

Fundamental Scientific Computing

Data Manipulation and Analysis

Matplotlib

Plotting and Visualization

Scikit-learn

Statistical Data Visualization

Seaborn

Plotly and Cuflinks

Tkinter

Mongo DB

Flask rest api module

Webscraping

Statistics Module1

Statistics Module2

EDA

Machine Learning using SKlearn

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