The Complete Python Data Analysis and Visualization Course
The Complete Python Data Analysis and Visualization Course, available at $44.99, has an average rating of 4.55, with 59 lectures, 4 quizzes, based on 23 reviews, and has 90 subscribers.
You will learn about Fundamentals of Python Programming Learn Exploratory Data Analysis Use Python Numpy library to adding support for large, multi-dimensional arrays and matrices Use the Python Pandas library to create and structure data Create data visualizations using Python matplotlib and the seaborn libraries 20-Data Analysis Interview Questions 20-Python Interview Questions Use of Jupyter Notebook Environment This course is ideal for individuals who are Beginners Data Scientists. or IT Managers eager to learn Data Analysis and Visualization. or Anyone interested in learning more about Python, Data science, or Data visualizations. or Anyone interested about the rapidly expanding world of data science! or Anyone want to spend leisure time in expanding his/her Data analysis and visualization skills. It is particularly useful for Beginners Data Scientists. or IT Managers eager to learn Data Analysis and Visualization. or Anyone interested in learning more about Python, Data science, or Data visualizations. or Anyone interested about the rapidly expanding world of data science! or Anyone want to spend leisure time in expanding his/her Data analysis and visualization skills.
Enroll now: The Complete Python Data Analysis and Visualization Course
Summary
Title: The Complete Python Data Analysis and Visualization Course
Price: $44.99
Average Rating: 4.55
Number of Lectures: 59
Number of Quizzes: 4
Number of Published Lectures: 59
Number of Published Quizzes: 4
Number of Curriculum Items: 63
Number of Published Curriculum Objects: 63
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Fundamentals of Python Programming
- Learn Exploratory Data Analysis
- Use Python Numpy library to adding support for large, multi-dimensional arrays and matrices
- Use the Python Pandas library to create and structure data
- Create data visualizations using Python matplotlib and the seaborn libraries
- 20-Data Analysis Interview Questions
- 20-Python Interview Questions
- Use of Jupyter Notebook Environment
Who Should Attend
- Beginners Data Scientists.
- IT Managers eager to learn Data Analysis and Visualization.
- Anyone interested in learning more about Python, Data science, or Data visualizations.
- Anyone interested about the rapidly expanding world of data science!
- Anyone want to spend leisure time in expanding his/her Data analysis and visualization skills.
Target Audiences
- Beginners Data Scientists.
- IT Managers eager to learn Data Analysis and Visualization.
- Anyone interested in learning more about Python, Data science, or Data visualizations.
- Anyone interested about the rapidly expanding world of data science!
- Anyone want to spend leisure time in expanding his/her Data analysis and visualization skills.
This course will give you the resources to learn python and effectively use it analyze and visualize data! Start your career in Data Science!
You’ll get a full understanding of how to program with Python and how to use it in conjunction with scientific computing modules and libraries to analyze data.
By the end of this course you will:
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Have an understanding of how to program in Python.
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Know how to create and manipulate arrays using Numpy and Python.
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Know how to use Pandas to create and analyze data sets.
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Know how to use Matplotlib and Seaborn libraries to create beautiful data visualization.
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Grasp the theoretical and practical concepts parallel
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Have hands-on experience on KFC data set
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Have an amazing portfolio of example python data analysis projects!
With 30+ lectures and over 10+ labs, you will be excellently prepared for a future in data science!
So what are you waiting for? Get Enrolled in this course
Course Curriculum
Chapter 1: UNBOXING DATA ANALYSIS AND PYTHON
Lecture 1: What is Data Analysis and Data Visualization?
Lecture 2: Why Python and Data Analysis?
Lecture 3: What is Data Wrangling and Data Cleaning?
Chapter 2: SETTING UP PYTHON ENVIRONMENT
Lecture 1: Installing Python on Windows
Lecture 2: Installing Python on Linux
Lecture 3: Installing Python on Mac
Lecture 4: Installing Anaconda on Windows
Chapter 3: PYTHON PRIMER
Lecture 1: Syntax
Lecture 2: Data Types
Lecture 3: Variables
Lecture 4: Comments
Lecture 5: Exception Handling
Chapter 4: WORKING WITH DATA STRUCTURES
Lecture 1: Standard Data Structures
Lecture 2: List
Lecture 3: Tuple
Lecture 4: Dictionary
Lecture 5: Set
Chapter 5: DATA FORMATS AND SOURCES
Lecture 1: Data Formats
Lecture 2: Importing Data Sets From Public Sources
Lecture 3: Importing Data Sets From Facebook
Chapter 6: DATA PREPARATION (NUMPY)
Lecture 1: Introduction to Numpy
Lecture 2: Data Types
Lecture 3: Arrays
Lecture 4: Array Functions
Lecture 5: Operations on Arrays
Lecture 6: LAB: Numpy
Chapter 7: DATA PREPARATION (PANDAS)
Lecture 1: Data Preparation
Lecture 2: Loading and Saving Data
Lecture 3: Pandas Functions
Lecture 4: Regular Expression
Lecture 5: LAB: Pandas
Lecture 6: LAB: Regular Expression
Chapter 8: EXPLORATORY DATA ANALYSIS
Lecture 1: Introduction to Exploratory Data Analysis
Lecture 2: Types of Statistical Data
Lecture 3: Data Profiling
Lecture 4: Data Cleaning
Lecture 5: Missing Values
Lecture 6: LAB: EDA and Missing Values
Lecture 7: Outliers
Lecture 8: LAB: Outliers
Lecture 9: Statistical Methods
Lecture 10: Indexing and Retrieving
Lecture 11: Data Normalization
Lecture 12: Binning and Correlation
Lecture 13: LAB: Binning
Lecture 14: LAB: Correlation
Lecture 15: Grouping Data
Lecture 16: LAB: Grouping
Lecture 17: LAB: Creating Columns
Chapter 9: DATA VISUALIZATION
Lecture 1: Data Visualization
Lecture 2: Matplotlib
Lecture 3: LAB: Matplotlib
Lecture 4: Seaborn
Lecture 5: LAB: Seaborn
Lecture 6: LAB: Exploratory Data Analysis on Titanic Data set
Chapter 10: GETTING READY FOR DA AND PYTHON WORLD
Lecture 1: Career Path and Road map
Lecture 2: 20 Data Analysis Interview Questions
Lecture 3: 20 Python Interview Questions
Chapter 11: CAPSTONE PROJECT
Lecture 1: KFC
Instructors
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SKILL CURB
TECHNOLOGY MADE EASY
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 2 votes
- 3 stars: 1 votes
- 4 stars: 6 votes
- 5 stars: 13 votes
Frequently Asked Questions
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