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Data Analytics & Visualization: Using Excel and Python

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Data Analytics & Visualization: Using Excel and Python, available at $19.99, has an average rating of 4.46, with 125 lectures, 23 quizzes, based on 366 reviews, and has 26125 subscribers.

You will learn about Real-world use cases of Python and its versatility. Installation of Python on both Mac and Windows operating systems. Fundamentals of programming with Python, including variables and data types. Working with various operators in Python to perform operations. Fundamental concepts and importance of statistics in various fields. How to use statistics for effective data analysis and decision-making. Introduction to Python for statistical analysis, including data manipulation and visualization. This course is ideal for individuals who are Beginners with no prior programming experience. or Students or professionals in various fields, including business, science, social sciences, and healthcare, who want to enhance their data analysis skills. or Anyone interested in automating tasks or data analysis. or Data analysts, researchers, and scientists seeking to strengthen their statistical foundations and Python programming skills. or Beginners with no prior statistical knowledge but with a curiosity to learn and apply statistical methods. or Professionals looking to advance their career by acquiring valuable statistical and data analysis skills. It is particularly useful for Beginners with no prior programming experience. or Students or professionals in various fields, including business, science, social sciences, and healthcare, who want to enhance their data analysis skills. or Anyone interested in automating tasks or data analysis. or Data analysts, researchers, and scientists seeking to strengthen their statistical foundations and Python programming skills. or Beginners with no prior statistical knowledge but with a curiosity to learn and apply statistical methods. or Professionals looking to advance their career by acquiring valuable statistical and data analysis skills.

Enroll now: Data Analytics & Visualization: Using Excel and Python

Summary

Title: Data Analytics & Visualization: Using Excel and Python

Price: $19.99

Average Rating: 4.46

Number of Lectures: 125

Number of Quizzes: 23

Number of Published Lectures: 120

Number of Published Quizzes: 22

Number of Curriculum Items: 149

Number of Published Curriculum Objects: 142

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

  • Real-world use cases of Python and its versatility.
  • Installation of Python on both Mac and Windows operating systems.
  • Fundamentals of programming with Python, including variables and data types.
  • Working with various operators in Python to perform operations.
  • Fundamental concepts and importance of statistics in various fields.
  • How to use statistics for effective data analysis and decision-making.
  • Introduction to Python for statistical analysis, including data manipulation and visualization.

Who Should Attend

  • Beginners with no prior programming experience.
  • Students or professionals in various fields, including business, science, social sciences, and healthcare, who want to enhance their data analysis skills.
  • Anyone interested in automating tasks or data analysis.
  • Data analysts, researchers, and scientists seeking to strengthen their statistical foundations and Python programming skills.
  • Beginners with no prior statistical knowledge but with a curiosity to learn and apply statistical methods.
  • Professionals looking to advance their career by acquiring valuable statistical and data analysis skills.

Target Audiences

  • Beginners with no prior programming experience.
  • Students or professionals in various fields, including business, science, social sciences, and healthcare, who want to enhance their data analysis skills.
  • Anyone interested in automating tasks or data analysis.
  • Data analysts, researchers, and scientists seeking to strengthen their statistical foundations and Python programming skills.
  • Beginners with no prior statistical knowledge but with a curiosity to learn and apply statistical methods.
  • Professionals looking to advance their career by acquiring valuable statistical and data analysis skills.

Embark on a transformative journey into the dynamic realm of Data Analytics and Visualization, where you will acquire essential and sought-after tech skills. This comprehensive course is designed to empower you with proficiency in key tools and methodologies, including Python programming, Excel, statistical analysis, data analysis, and data visualization.

Key Learning Objectives:

– Gain hands-on experience in Python, a powerful and versatile programming language widely used for data analysis and manipulation.

– Learn to leverage Python libraries such as Pandas and NumPy for efficient data handling and manipulation.

– Develop advanced skills in Excel, exploring its robust features for data organization, analysis, and visualization.

– Harness the power of Excel functions and formulas to extract insights from complex datasets.

– Acquire a solid foundation in statistical concepts and techniques essential for making informed decisions based on data.

– Apply statistical methods to interpret and draw meaningful conclusions from data sets.

– Explore the entire data analysis process, from data cleaning and preprocessing to exploratory data analysis (EDA) and feature engineering.

– Learn how to identify patterns, outliers, and trends within datasets, enabling you to extract valuable insights.

– Master the art of presenting data visually through a variety of visualization tools and techniques.

– Use industry-standard tools like Matplotlib and Seaborn to create compelling and informative data visualizations.

Upon completion, you will possess a well-rounded skill set in data analytics and visualization, equipping you to tackle real-world challenges and contribute meaningfully to data-driven decision-making in any professional setting. Join us on this journey to become a proficient and sought-after tech professional in the field of data analytics and visualization.

Course Curriculum

Chapter 1: Fundamentals of Excel

Lecture 1: Excel Applications

Lecture 2: Understanding the Excel Interface

Lecture 3: Sorting and Filtering

Lecture 4: Conditional Formatting

Chapter 2: Statistical and Mathematical Functions in Excel

Lecture 1: Introductions to Statistical Functions

Lecture 2: Introduction to Mathematical Functions

Chapter 3: Lookup functions, and Pivot Tables

Lecture 1: Introduction to Lookup Functions

Lecture 2: Introduction to Index and Match

Lecture 3: Introduction to Pivot Tables

Lecture 4: Introduction to Pivot Charts

Chapter 4: Logical Functions, and Text Functions

Lecture 1: Introduction to Logical Function

Lecture 2: Formatting Cells based on Logical Functions

Lecture 3: Introduction to Text Functions

Lecture 4: Formatting cells based on Text Functions

Chapter 5: Data Cleaning, and Feature engineering

Lecture 1: Introduction to Date and Time Functions

Lecture 2: Basics of Data Cleaning in Excel

Lecture 3: Basics of Feature Engineering in Excel

Lecture 4: Introduction to Power Query in Excel

Chapter 6: What If analysis

Lecture 1: Scenario Manager

Lecture 2: Goal Seek

Lecture 3: Data Tables

Lecture 4: Solver Package

Chapter 7: Charts and Dashboards

Lecture 1: Data Visualization Best Practices

Lecture 2: Types of Charts in Excel

Lecture 3: Creating and Formatting Charts

Chapter 8: Linear Regression and Forecasting

Lecture 1: Introduction to Linear Regression…

Lecture 2: Preliminary Forecasting Analysis….

Chapter 9: Basics of Python

Lecture 1: Real world use cases of Python

Lecture 2: Installation of Anaconda for Windows and macOS

Lecture 3: Introduction to Variables

Lecture 4: Introduction to Data Types and Type Casting

Lecture 5: Scope of Variables

Lecture 6: Introduction to Operators

Chapter 10: Introduction to Data Structures

Lecture 1: Introduction to Lists and Tuples

Lecture 2: Introduction to Sets and Dictionaries

Lecture 3: Introduction to Stacks and Queues

Lecture 4: Introduction to Space and Time Complexity

Lecture 5: Introduction to Sorting Algorithms

Lecture 6: Introduction to Searching Algorithms

Chapter 11: Introduction to Functions in Python

Lecture 1: Introduction to Parameters and Arguments

Lecture 2: Introduction to Python Modules

Lecture 3: Introduction to Filter, Map, and Zip Functions

Lecture 4: Introduction to List, Set and Dictionary Comprehensions

Lecture 5: Introduction to Lambda Functions

Lecture 6: Introduction to Analytical and Aggregate Functions

Chapter 12: Strings and Regular Expressions

Lecture 1: Introduction to Strings

Lecture 2: Introduction to Important String Functions

Lecture 3: Introduction to String Formatting and User Input

Lecture 4: Introduction to Meta Characters

Lecture 5: Introduction to Built-in Functions for Regular Expressions

Lecture 6: Special Characters and Sets for Regular Expressions

Chapter 13: Loops and Conditionals

Lecture 1: Introduction to Conditional Statements

Lecture 2: Introduction to For Loops

Lecture 3: Introduction to While Loops

Lecture 4: Introduction to Break and Continue

Lecture 5: Using Conditional Statements in Loops

Lecture 6: Nested Loops and Conditional Statements

Chapter 14: OOPs and Date-Time

Lecture 1: Introduction to OOPs Concept

Lecture 2: Introduction to Inheritance

Lecture 3: Introduction to Encapsulation

Lecture 4: Introduction to Polymorphism

Lecture 5: Introduction to Date and Time Class

Lecture 6: Introduction to TimeDelta Class

Chapter 15: Introduction to Statistics

Lecture 1: Introduction to Statistics and its importance

Lecture 2: Explain the role of statistics in data analysis

Lecture 3: Introduction to Python for Statistical Analysis

Chapter 16: Introduction to Descriptive Statistics

Lecture 1: Types of Data

Lecture 2: Measures of Central Tendency

Lecture 3: Measures of Spread

Lecture 4: Measures of Dependence

Instructors

Rating Distribution

  • 1 stars: 4 votes
  • 2 stars: 5 votes
  • 3 stars: 31 votes
  • 4 stars: 117 votes
  • 5 stars: 209 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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