Python Programming
Course in Pune
with 100% Placement Assistance

Course Overview:

Welcome to the Comprehensive Python Programming course by MindScripts Tech, where this course will provide a comprehensive introduction to the fundamental concepts and techniques of data science using Python programming language. Participants will learn how to analyze and visualize data, build predictive models, and extract valuable insights from large datasets.

Key Features:

1. Hands-on Learning: The course emphasizes practical, hands-on exercises and real-world projects to ensure participants gain valuable experience in applying data science concepts using Python.

2. Comprehensive Curriculum: Covering fundamental concepts to advanced topics, the course provides a comprehensive understanding of data science, including data manipulation, visualization, statistical analysis, machine learning, and deep learning.

3. Python-centric Approach: Focused on leveraging Python programming language, participants learn to utilize popular libraries such as Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn for data manipulation, analysis, visualization, and machine learning tasks.

4. Expert Instructors: Led by experienced instructors with expertise in data science and Python programming, participants receive guidance and mentorship throughout the course to enhance their learning experience.

5. Practical Projects: The course includes a capstone project where participants apply their knowledge and skills to solve a real-world data science problem, providing valuable experience and showcasing their abilities to potential employers.

6. Flexibility: Designed to accommodate both beginners and those with some prior experience in data science and Python programming, the course offers flexibility in pacing and difficulty level, allowing participants to progress at their own pace.

7. Interactive Learning Environment: Through a combination of lectures, demonstrations, discussions, and interactive coding sessions, participants engage actively in the learning process, fostering better understanding and retention of concepts.

8. Career Development: The course not only equips participants with technical skills but also provides guidance on career development aspects, including resume building, interview preparation, and job search strategies in the field of data science.

9. Continued Learning Resources: Beyond the course duration, participants gain access to additional resources, including reading materials, online tutorials, and community forums, to continue their learning and stay updated with the latest advancements in data science and Python.

Python is one of the most in-demand programming languages in India, widely used in fields like Data Science, AI, Web Development, and Automation.

Course Syllabus:

Python Operators

• What is Python programming language?

• Advantages and applications of Python

• Installation of Python

• Python Keywords

• The statement, Indentation, and Comment in Python

• Rule of Variables in Python

Introduction to Python

• What are operators in Python?

• Types of operators

• Arithmetic operator

• Assignment operator

• Comparison operator

• Logical operator

• Bitwise operator

• Special operators

• Ternary Operator

Python Data Types

Lists in Python

• Knowing the size of the list

• Adding elements to a list

• Accessing elements from the list

• Delete or Remove elements from the list

• Slicing of a list

• Iterating a list

• List Comprehension

• Nested list

• List Methods

File Handling

• Get the Type of data type

• NumbersPython String

• Python List

• Python Tuples

• Python Sets

• Python Dictionary

• Type Conversion

Python Control Flow

• Python Conditional statements

• Python For Loop

• Python While Loop

• Python break statement

• Python continue statement

• Python pass statement

Python Strings

• Access characters/elements in a string

• Concatenation of two or more string

• String Slicing

• Iterating string

• Delete or Change String

• String Formatting

• String Methods

• Escape Characters

• Open a file in Python

• Close a file in Python

• Write to file in Python

• Read files in Python

• Python directory and files management

Conditional Statements

• Conditional Statements & Loop Conditional Statements

• (If, If-else, If-elif-else, Nested-if etc.) and

• loop control statements (for, while,

• Nested loops, Break, Continue, Pass statements)

Python Pickle

• Introduction to Pickle

• Storing Data with Pickles

• Pickling files

• Unpickling files

Python Tkinter

• Introduction to Tkinter

• Widgets in Tkinter

• Geometry Management

• Organizing Layout and Widgets

• Binding Functions

• Mouse Clicking Events

• Drop-Down Menus

• Alert Box

• Simple Shapes

• Image and Icons

Data Visualization using Matplotlib

• Introduction, plot(),Controlling Line Properties, Subplotwith Functional Method, Multiple Plot,Working with Multiple Figures,Histograms

Python Tuples

• Accessing elements in a Tuple

• Tuple Slicing

• Update Tuple

• Unpack Tuple

• Concatenation of Tuples

• Changing and deleting Tuples

• Python Tuple Methods

Dictionary in Python

• Accessing Elements from a Dictionary

• Add/Change Elements in a Dictionary

• Nested Dictionary

• Deleting Elements from Dictionary

• Dictionary Methods

Sets in Python

• Adding Elements to a Set

• Accessing a Set

• Removing Elements from a Set

• Set Methods

Python Functions

• Syntax of Function

• Types of Functions

• Doc, string

• Arguments

• Recursion in Python

• Python Recursive Function

• Lambda functions in Python

• Modules in python

• Packages

Python OOP

• Class

• Object

• Inheritance

• iterators

• Encapsulation

• Polymorphism

• Python Objects and Class

• Constructors in Python

• Deleting Attributes and objects

• Multiple Inheritance

• Multilevel Inheritance

Exception Handling in Python

• Syntax Error

• Exceptions

• Try and Accept in Exception Handling

• Raising Exception

• Python Errors and Built-in Exceptions

Data Visualization using Seaborn

• Introduction to Seaborn and Visualizing statistical relationships, Import and Prepare data. Plotting with categorical data and Visualizing linear relationships.

• Seaborn Exercise

Data Analysis Using Pandas

• Pandas : Introduction to Pandas

• Importing data into Python

• Pandas Data Frames, Indexing DataFrames, Basic Operations With Dataframe, Renaming Columns, Subsetting and filtering a data frame

Data Analysis Using Numpy

• Introduction to Numpy. Array Creation, Printing Arrays, BasicOperation - Indexing, Slicing and iterating, Shape Manipulation -Changing shape, stacking and splitting of array

• Vector stacking, Broadcasting with Numpy, Numpy for Statistical Operation

Fundamentals of Math and Probability

• Probability distributed function & cumulative distribution function. Conditional Probability, Baye’sTheorem

• Problem solving for probability assignments

• Random Experiments, Mutually Exclusive Events, Joint Events, Dependent & Independent Events

Data Processing & Exploratory Data Analysis

• What is Data Wrangling

• Data Pre-processing and cleaning?

• How to Restructure the data?

• What is Data Integration and transformation

Introduction to Database (SQL)

• Introduction

• Database Fundamentals

• SQL Essentials

• Installation of MySQL

• Exploring SQL Statements

• SQL Query Basics

• Advanced SQL Concepts

Django

• Introduction to Django

• Difference between an App and Project

• Understanding Migrations and their purpose

• Admin Part: Creating a Superuser in Python

• Views in Django URL Routing

• Render and Relative Import

• Overview of Settings File in Django

• Configuring Templates in Django

• Understanding Models

• Linking Models to Admin

• Creating Model Forms

• Form Validation in Django

• Context in Django

• Forms in a view

• Custom Forms

• Setting up Email in Projects

• Static Files and Serving in Django

• Bootstrap Grid System

• Introduction to CSS and Blocks

• URL Names as Links

• Adding Authentication in Django Project

• Authentication Links in Navigation Bar

• Adding Login Form in Bootstrap

• Query Set Basics

• Rendering Images and Videos on our site

MongoDB

• What is MongoDB?

• Characteristics and Features

• MongoDB Ecosystem

• Installation process

• Connecting to MongoDB database

• Introduction to NoSQL

• Introduction of MongoDB module

• What are Object IDs in MongoDB

• MongoDB Use cases

• MongoDB Structures

• MongoDB Shell vs MongoDB Server

• Data Formats in MongoDB

• MongoDB Aggregation Framework

• Aggregating Documents

• Working with MongoDB Compass & exploring data visually

• Understanding Create, Read, Update, Delete

• Schemas & Relations

• Document Structure

Tools Covered:

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