Beginner to Pro- Python for Data Analytics Course 2024

Beginner to Pro: Python for Data Analytics Course 2024, available at $54.99, with 40 lectures, and has 1 subscribers.

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

Enroll now: Beginner to Pro: Python for Data Analytics Course 2024

Summary

Title: Beginner to Pro: Python for Data Analytics Course 2024

Price: $54.99

Number of Lectures: 40

Number of Published Lectures: 40

Number of Curriculum Items: 40

Number of Published Curriculum Objects: 40

Original Price: $109.99

Quality Status: approved

Status: Live

What You Will 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.

Who Should Attend

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 todays data-driven world.

Target Audiences

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 todays data-driven world.

“Beginner to Pro: Python Programming for Data Analytics Course” is a comprehensive program tailored for beginners eager to harness the power of Python programming for data analytics. In today’s data-driven world, proficiency in manipulating and deriving insights from data is essential across diverse fields. This course serves as a foundational starting point, systematically breaking down complex programming concepts into manageable steps.

Participants will embark on an educational journey through Python programming, beginning with fundamental concepts and progressing to advanced techniques relevant to data analytics:

Python Basics: Covering variables, data types (such as integers, floats, strings), operators, and basic input/output in Python programming.

Control Structures: Including conditional statements (if, elif, else) and loops (for, while) for flow control in Python programming.

Functions: Defining and using functions to encapsulate reusable pieces of code in Python programming.

Data Structures: Exploring lists, tuples, sets, and dictionaries for storing and manipulating collections of data in Python programming.

File Handling: Reading from and writing to files to manage data persistence using Python programming.

Data Cleaning: Techniques for preprocessing data ensure accuracy and reliability in subsequent analyses using Python programming.

Data Analysis: Methods for exploring and summarizing data facilitate understanding patterns and trends, essential for informed decision-making with Python programming.

One of the highlights of the course is a practical project where participants apply the learned concepts to analyze Twitter data. This project allows them to:

Collect and preprocess real-time Twitter data using Python programming techniques.

Analyze trends, sentiments, and interactions from Twitter data sets using Python programming libraries.

Present findings and insights from Twitter data analysis effectively using data visualization tools like Matplotlib.

Throughout the course, practical exercises and real-world examples guided by experienced instructors will solidify participants’ understanding of Python programming fundamentals for data analytics. By course completion, participants will have acquired foundational skills in Python programming for data manipulation and analysis, equipping them to confidently address data challenges in their respective domains.

“Unlocking Insights with Python Programming” offers a streamlined pathway for beginners to master Python programming for data analytics, emphasizing practical application and real-world relevance, particularly through hands-on projects like Twitter data analysis.

Happy Learning!!! 馃檪

Course Curriculum

Chapter 1: Introduction to Python Programming & its Environment

Lecture 1: 1. Motivation for learning Python

Lecture 2: 2. Python Introduction

Lecture 3: 3. Introduction_Anaconda

Lecture 4: 4. Anaconda Installation

Lecture 5: 5. Introduction to Jupyter Notebook Interface

Chapter 2: Introduction to Python Programming

Lecture 1: 1 Syntax_in_Programming

Lecture 2: 2 Newline Character

Lecture 3: 3 Elements_Keywords_Identifiers

Lecture 4: 4.Comments_Statement

Lecture 5: 5 Variable Assignment

Lecture 6: 6 Data Type I in Python Programming

Lecture 7: 7. Data Type II

Lecture 8: 8 Type Conversion of Data Type

Lecture 9: 9 Output Formatting and Input Function

Lecture 10: 10 Operators in Python Programming

Lecture 11: 11 IF Statements

Lecture 12: 12 While loop Statements

Lecture 13: 13 For loop Statement

Lecture 14: 14 Break and Continue Statement

Lecture 15: 15 Lists-I

Lecture 16: 16 Lists-II

Lecture 17: 17 Tuples

Lecture 18: 18 Strings

Lecture 19: 19 Sets

Lecture 20: 20 Dictionary

Lecture 21: 21 Functions

Lecture 22: 22 Function Arguments and parameters

Lecture 23: 23 Built-in Functions

Lecture 24: 24 Recursive Function

Lecture 25: 25 Lambda Function

Lecture 26: 26 Modules,Package,libraries

Lecture 27: 27 File IO Operation

Lecture 28: 28 Working with Python directory and files

Lecture 29: 29 Exception handling with python

Lecture 30: 30 Comprehension in Python

Lecture 31: Project 1- Twitter Data Analysis

Lecture 32: Project 2- Twitter Data Analysis

Lecture 33: Project 3- Twitter Data Analysis

Lecture 34: Project 4- Twitter Data Analysis

Lecture 35: Project 5- Twitter Data Analysis

Instructors

Ganeshraj Shetty
Instructor @ Udemy

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Frequently Asked Questions

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