Python Hands-on (with SQLite, NumPy, Networking, Pandas)

Python Hands-on (with SQLite, NumPy, Networking, Pandas), available at $34.99, has an average rating of 3.75, with 60 lectures, based on 158 reviews, and has 20177 subscribers.

You will learn about The students will be able to program in python, solve problems, develop own python programs This course is ideal for individuals who are Non programmers, C/C++ programmers, java, javascript programmers. This course is meant typically for those who want to learn python, like freshers. or This course is meant typically for those who want to learn python, like freshers. It is particularly useful for Non programmers, C/C++ programmers, java, javascript programmers. This course is meant typically for those who want to learn python, like freshers. or This course is meant typically for those who want to learn python, like freshers.

Enroll now: Python Hands-on (with SQLite, NumPy, Networking, Pandas)

Summary

Title: Python Hands-on (with SQLite, NumPy, Networking, Pandas)

Price: $34.99

Average Rating: 3.75

Number of Lectures: 60

Number of Published Lectures: 60

Number of Curriculum Items: 60

Number of Published Curriculum Objects: 60

Original Price: ₹799

Quality Status: approved

Status: Live

What You Will Learn

The students will be able to program in python, solve problems, develop own python programs

Who Should Attend

Non programmers, C/C++ programmers, java, javascript programmers. This course is meant typically for those who want to learn python, like freshers.
This course is meant typically for those who want to learn python, like freshers.

Target Audiences

Non programmers, C/C++ programmers, java, javascript programmers. This course is meant typically for those who want to learn python, like freshers.
This course is meant typically for those who want to learn python, like freshers.

The course is divided into mainly two parts: basics and advanced.

A person who is beginner or never have done programming can benefit from the course. Those folks who have done some amount of programming can take good benefit of basic topics (Variables, Strings, List, Condition, Loops, Functions, Dictionary, Tuples, File Handling, JSON, Exceptions, Comprehension like List, Dictionary, Tuple ) , advanced topics (Iterator, Generator, Regular Expression, Networking, Web Interaction, Database, SQL, SQLite, Database: Single table, multiple tables, Multi-threading, Multi processing, Custom Modules ), Object Oriented Programming (Classes and Objects, Inheritance, Exceptions, Iterator) and Numpy.

All these topics are taught as concept and hands-on practicals. Python has exponentially growing community around data science, machine learning, web development and more. Python is a language that opens programming access to the world. Python is considered easy to read, write and learn. Plus, it’s extremely scalable.

Those students who wish to pursue further courses like Machine Learning, Data Science and Deep Learning will definitely benefit from this course as python happens to form the basis for such courses.

The course contents are:

Python

Why python?
Installation of Development Environment
Variables, Strings, List
Condition, Loops,
Functions
Dictionary
Tuples
File Handling
JSON
Exceptions
Comprehension (List, Dictionary, Tuple)

Advanced Topics

Iterator
Generator
Regular Expression
Networking, Web Interaction
Database, SQL, SQLite
Database: Single table, multiple tables
Multi-threading,
Multi processing
Custom Modules

Objected Oriented Programming

Classes and Objects
Inheritance
Exceptions
Iterator

NumPy

Numpy array operations
Indexing
Slicing
Stacking

Various hands-on practicals and exercises are also provided as part of recordings. The python programs (code) are provided as resources to various hands-on / practical videos.

Course Curriculum

Chapter 1: Python Programming

Lecture 1: Intro & Course Contents

Lecture 2: Development Environment and Installation

Lecture 3: Variables and Numbers in Python (with Practical)

Lecture 4: Strings in Python (with Practical)

Lecture 5: Lists in Python (with Practical)

Lecture 6: Conditional Execution (with Practical)

Lecture 7: Loops (with Practical)

Lecture 8: Functions (with Practical)

Lecture 9: Dictionaries in Python (with Practical)

Lecture 10: Tuples in Python (with Practical)

Lecture 11: Exceptions and it's Handling

Lecture 12: Exceptions and it's Handling (with Practical)

Lecture 13: Iterators (with Strings, List, Dictionary, Tuple)

Lecture 14: Iterators Practical (with Strings, List, Dictionary, Tuple)

Lecture 15: Comprehension – List, Dictionary (with Practical)

Lecture 16: Comprehension – Sets (with Practical)

Lecture 17: File Support (with Practical) – part 1

Lecture 18: File Support (with Practical) – part 2

Lecture 19: JSON support (with Practical)

Chapter 2: Advanced Python Programming

Lecture 1: Regular Expression with practical (part 1)

Lecture 2: Regular Expression with practical (part 2)

Lecture 3: Networking, Web Access with practical (part 1)

Lecture 4: Networking, Web Access with practical (part 2)

Lecture 5: Database, SQL, SQLite interaction (part 1)

Lecture 6: Database, SQL, SQLite interaction (part 2)

Lecture 7: Create Database, Table(s) with Practical

Lecture 8: Insert data (records) to Table with Practical

Lecture 9: Read data (records) from Table with Practical

Lecture 10: Update data (records) in Table, Delete data (records) from Table with Practical

Lecture 11: Multiple Tables, Join query with Practical

Lecture 12: Module- Custom Module

Lecture 13: Multi Threading and Multi Processing (part 1)

Lecture 14: Multi Threading and Multi Processing (part 2)

Chapter 3: OO – Object Oriented Programming

Lecture 1: OO- Classes Objects, Inheritance

Lecture 2: OO- Classes Objects, Inheritance with Practical

Lecture 3: OO- Custom Exceptions

Lecture 4: OO- Custom Iterator , Generator functions

Chapter 4: NumPy

Lecture 1: NumPy with Practical (part 1)

Lecture 2: NumPy with Practical (part 2)

Chapter 5: Pandas Basics

Lecture 1: Pandas Course Contents

Lecture 2: Some more Contents

Lecture 3: Datascience short introduction

Lecture 4: Jupyter notebook Demo

Lecture 5: File (csv) read – Demo

Lecture 6: File write (csv) – Demo

Lecture 7: Missing data, Wrangling/Filtering – 1

Lecture 8: Missing data, Wrangling/Filtering – 2

Lecture 9: GroupBy – Demo

Lecture 10: Dataframes Concatenation – Demo

Lecture 11: MySQL – Overview

Lecture 12: MySQL – Pandas Demo

Chapter 6: Pandas Advanced

Lecture 1: Dataframes Merging – Demo

Lecture 2: Pivot Table support – Demo

Lecture 3: Excel (xlsx files) support – Demo

Lecture 4: Stack / UnStack support

Lecture 5: Stack / UnStack – Demo

Lecture 6: Cross Tab – Demo

Lecture 7: ReShaping – Demo

Lecture 8: Time Series (Stock data) Calendar, Holidays – Demo

Lecture 9: Time Series (Stock data) Resampling – Demo

Instructors

Shrirang Korde
Technologist

Rating Distribution

1 stars: 1 votes
2 stars: 11 votes
3 stars: 29 votes
4 stars: 60 votes
5 stars: 57 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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