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A Non-Programmer'S Guide To Python For Analytics

A Non-Programmer'S Guide To Python For Analytics

A Non-Programmer'S Guide To Python For Analytics
Published 4/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English

| Size: 6.71 GB[/center]
| Duration: 10h 18m
Unlocking Insights with Python: A Step-by-Step Guide for Non-Programmers

What you'll learn

Students will master the fundamentals of Python programming language, covering topics such as syntax, variables, data types, and control structures.

Learners will understand essential data structures in Python, including lists, tuples, dictionaries, and sets, and learn how to manipulate and iterate over them

Participants will explore how to define and use functions to modularize code and increase reusability, as well as how to import and work with modules in Python.

Students will learn how to read from and write to files in Python, enabling them to interact with external data sources and store program output.

Learners will grasp the concept of exception handling in Python and learn how to use try-except blocks to handle errors gracefully & maintain program stability.

A project through which students will apply their Python programming skills to solve real-world problems and reinforce their learning.

Requirements

As it is a beginners course there are no prerequisites.

Description

Demystifying dаta: Unlocking Insights with Python" is a comprehensive course designed for non-programmers eager to harness the power of Python for data analytics. In today's data-driven world, understanding how to manipulate and derive insights from data is essential for success across various fields. This course serves as an accessible entry point, breaking down complex programming concepts into manageable steps.Participants will embark on a journey through Python, starting from the basics and gradually advancing to more sophisticated techniques. With a focus on practical application, learners will explore how to collect, clean and analyze data using Python programming concepts taught in the course.Guided by experienced instructor, students will gain hands-on experience through interactive exercises and real-world examples, solidifying their understanding of key concepts without requiring prior programming experience.By the end of the course, participants will have developed a foundational understanding of Python programming for data analytics, empowering them to confidently tackle data-related challenges and make informed decisions in their respective domains. Join us on this journey and unlock the potential of data with Python!Unlocking Insights with Python" is a comprehensive, time-efficient course designed for non-programmers, offering a streamlined path to mastering Python for data analytics.Enroll today to make the right start to the field of Data Analytics and Machine Learning.Happy Learning!!! :)

Overview

Section 1: Introduction to Python Programming

Lecture 1 1. Motivation for learning Python

Lecture 2 2. Python Introduction

Lecture 3 3. Intro_Anaconda_JupyterNB

Lecture 4 4. Anaconda Installation

Lecture 5 5. Intro to Jupyter Notebook interface

Section 2: Introduction

Lecture 6 1 Syntax_in_Programming

Lecture 7 2 Newline Character

Lecture 8 3 Elements_Keywords_Identifiers

Lecture 9 4.Comments_Statement

Lecture 10 5 Variable Assignment

Lecture 11 6 Data Type I in Python Programming

Lecture 12 7. Data Type II

Lecture 13 8 Type Conversion of Data Type

Lecture 14 9 Output Formatting and Input Function

Lecture 15 10 Operators in Python Programming

Lecture 16 11 IF Statements

Lecture 17 12 While loop Statements

Lecture 18 13 For loop Statement

Lecture 19 14 Break and Continue Statement

Lecture 20 15 Lists-I

Lecture 21 16 Lists-II

Lecture 22 17 Tuples

Lecture 23 18 Strings

Lecture 24 19 Sets

Lecture 25 20 Dictionary

Lecture 26 21 Functions

Lecture 27 22 Function Arguments and parameters

Lecture 28 23 Built-in Functions

Lecture 29 24 Recursive Function

Lecture 30 25 Lambda Function

Lecture 31 26 Modules,Package,libraries

Lecture 32 27 File IO Operation

Lecture 33 28 Working with Python directory and files

Lecture 34 29 Exception handling with python

Lecture 35 30 Comprehension in Python

Lecture 36 Project 1- Twitter Data Analysis

Lecture 37 Project 2- Twitter Data Analysis

Lecture 38 Project 3- Twitter Data Analysis

Lecture 39 Project 4- Twitter Data Analysis

Lecture 40 Project 5- Twitter Data Analysis

Non-Programmers: This course is tailored specifically for individuals with little to no programming experience who are eager to delve into data analytics.,Professionals in Various Fields: Intended for professionals from diverse backgrounds such as business, healthcare, finance, marketing, and more.,Researchers and Academics: Ideal for researchers and academics looking to enhance their data analysis skills.,Students and Graduates: Suitable for students and recent graduates interested in gaining a competitive edge in the job market.,Lifelong Learners: Perfect for individuals with a passion for continuous learning and a desire to stay relevant in today's data-driven world.






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