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 today's 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 today's 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 today's 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 today's 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:
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Python Basics: Covering variables, data types (such as integers, floats, strings), operators, and basic input/output in Python programming.
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Control Structures: Including conditional statements (if, elif, else) and loops (for, while) for flow control in Python programming.
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Functions: Defining and using functions to encapsulate reusable pieces of code in Python programming.
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Data Structures: Exploring lists, tuples, sets, and dictionaries for storing and manipulating collections of data in Python programming.
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File Handling: Reading from and writing to files to manage data persistence using Python programming.
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Data Cleaning: Techniques for preprocessing data ensure accuracy and reliability in subsequent analyses using Python programming.
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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:
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Collect and preprocess real-time Twitter data using Python programming techniques.
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Analyze trends, sentiments, and interactions from Twitter data sets using Python programming libraries.
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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!!! 🙂
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
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Ganeshraj Shetty
Instructor @ Udemy
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Frequently Asked Questions
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Can I take my courses with me wherever I go?
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