Learning Python for Data Analysis and Visualization Ver 1 from Udemy

What's inside

Learning objectives

Have an intermediate skill level of python programming.
Use the jupyter notebook environment.
Use the numpy library to create and manipulate arrays.
Use the pandas module with python to create and structure data.

Learn how to work with various data formats within python, including: json,html, and ms excel worksheets.
Create data visualizations using matplotlib and the seaborn modules with python.
Have a portfolio of various data analysis projects.

Have an intermediate skill level of python programming.
Use the jupyter notebook environment.
Use the numpy library to create and manipulate arrays.
Use the pandas module with python to create and structure data.
Learn how to work with various data formats within python, including: json,html, and ms excel worksheets.
Create data visualizations using matplotlib and the seaborn modules with python.
Have a portfolio of various data analysis projects.

Syllabus

Understand what this course will help teach you.

Get a basic overview of what you will learn in this course.

Course FAQs

Have python and various modules set up on your computer.

Installation Setup and Overview

More course info

iPython/Jupyter Notebook Overview

Learn to use Numpy for array creation and manipulation.

Take a quick glance at the links in the text and then move on to the next lecture for the video lessons!

Learn to create arrays with numpy and Python.

Learn how to perform operations on multiple arrays and scalars!

Learn how to index arrays with numpy.

Learn several universal array functions in numpy.

Learn how to transpose arrays with numpy.

Learn different methods of processing arrays.

Learn how to import and export your arrays.

Learn to use pandas module in python to analyze data sets.

Learn about the Series data structure in pandas.

Learn about the DataFrame structure in pandas.

Important Note: If copying directly from Wikipedia does not work, paste the data into a word processor or NotePad Editor and then copy it from there and then run pd.read_clipboard()

Learn how to index Series and DataFrames in pandas.

Learn how to reindex in pandas.

Learn how to drop data entries in pandas.

Learn how to select particular entries in a pandas data structure.

Learn how to align your data in Python.

Learn how to rank and sort data entries.

Learn how to quickly get summary statistics in pandas.

Learn different ways of dealing with missing data in pandas.

Learn how to create hierarchical indexes in pandas.

Learn how to import load and store data in various formats.

Learn how to import and export text files with pandas.

Learn how to import and export JSON files with pandas.

Learn how to import HTML files with pandas.

NOTE: Install the following before this lecture, using either conda install or pip install:

pip install beautifulsoup4

pip install lxml

Learn how to import and export MS Excel files with pandas.

Learn how to transform and manipulate data.

Learn the basics of merging data sets.

Learn how to merge using an index.

Learn how to concatenate arrays,matrices, and DataFrames.

Learn how to combine DataFrames in pandas.

Learn how to reshape data sets.

Learn how to create Pivot tables with Python.

Learn how to take care of duplicate data entries.

Learn how to use mapping with pandas.

Learn how to replace data in pandas.

Learn how to rename indexes in pandas.

Learn how to use bins with pandas.

Learn how to find outliers in your data with pandas.

Learn how to use permutation with numpy and pandas.

Learn how to assemble separate data sets into a singular set

Learn how to use advanced groupby techniques.

Learn how to use the groupby method on Dictionaries and Series.

Learn about Data Aggregation with Python and pandas.

Learn about the powerful Split-Apply-Combine technique and how to use it in pandas.

Learn about cross-tabulation in pandas, a special case of pivot table!

Learn how to plot, visualize, and present data.

Quick overview on installing seaborn. Use "conda install seaborn" or "pip install seaborn".

Learn how to create histograms using seaborn and python.

Learn how to create kernel Density Estimation Plots with seaborn.

Learn how to combine histograms, KDE , and rug plots onto a single figure.

Learn how to create box and violin plots with seaborn.

Learn how to create regression plots in seaborn.

Learn how to create heatmaps with seaborn.

Use what you've learned to build a portfolio of data based projects.

Quick Preview for those interested in enrolling in the course!

Get an introduction to Github, Kaggle, and great public data sets!

Learn how to analyze the Titanic Kaggle Problem with Python, pandas, and seaborn!

Titanic Project - Part 2

Titanic Project - Part 3

Titanic Project - Part 4

Intro to Data Project - Stock Market Analysis

Data Project - Stock Market Analysis Part 1

Data Project - Stock Market Analysis Part 2

Data Project - Stock Market Analysis Part 3

Data Project - Stock Market Analysis Part 4

Data Project - Stock Market Analysis Part 5

Please Note: The second presidential debate was Oct 16 and not Oct 11. Oct 11 was the date of the Vice Presidential Debate!

Data Project - Election Analysis Part 1

Data Project - Election Analysis Part 2

Data Project - Election Analysis Part 3

Data Project - Election Analysis Part 4

Learn how to use scikit learn with Python!

Learn about the Pydata Ecosystem and SciKit Learn and what Machine Learning is all about!

Learn about the Math behind Linear Regression then implement it with SciKit Learn!

Linear Regression Part 2

Linear Regression Part 3

Linear Regression Part 4

Logistic Regression Part 1

Logistic Regression Part 2

Logistic Regression Part 3

Logistic Regression Part 4

Multi Class Classification Part 1 - Logistic Regression

Multi Class Classification Part 2 - k Nearest Neighbor

Support Vector Machines Part 1

Support Vector Machines - Part 2

Naive Bayes Part 1

Naive Bayes Part 2

Learn how to Use SciKit Learn for Decision Trees and Random Forests

Learn about Natural Language Processing!

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides a strong and in-depth look at using Python specifically for data analysis

Develops skills in working with numpy arrays, a fundamental data structure in Python data analysis

Covers pandas, a powerful and versatile Python library for data analysis and manipulation

Teaches data visualization using matplotlib and seaborn, two widely-used Python libraries for creating clear and informative visualizations

Builds a portfolio of data analysis projects, showcasing practical applications of the skills learned

Offers a comprehensive understanding of data analysis using Python

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Learning Python for Data Analysis and Visualization Ver 1 with these activities:

Read 'Introduction to Data Science'

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Gain a comprehensive understanding of the concepts and techniques of data science by reading the classic textbook 'Introduction to Data Science'.

View Mining of Massive Datasets on Amazon

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Read the book thoroughly, taking notes and highlighting key concepts.
Work through the exercises and examples provided in the book.

Review Python basics

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Review the basics of Python, such as data types, syntax, variables, and operators, to strengthen your foundation for learning data science.

Browse courses on Python Basics

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Go through your notes or study materials on Python basics.
Complete practice questions or exercises to test your understanding.

Follow tutorials on numpy and pandas

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Follow guided tutorials to learn the basics of numpy and pandas, which are essential libraries for data manipulation in Python.

Browse courses on NumPy

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Find reputable online tutorials or courses that cover numpy and pandas.
Work through the tutorials, taking notes and practicing the concepts.
Complete the exercises or assignments provided in the tutorials.

Three other activities

Expand to see all activities and additional details

Show all six activities

Create a data science portfolio

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Compile a portfolio that showcases your data science skills and projects to potential employers or clients.

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Select your best data analysis projects and prepare them for presentation.
Create a platform or online presence to host your portfolio.
Write brief descriptions and explanations for each project, highlighting your role and contributions.
Seek feedback from peers or mentors to refine and improve your portfolio.

Analyze a dataset of your choice

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Choose a dataset that interests you and analyze it using the skills and knowledge you've acquired in this course.

Browse courses on Data Exploration

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Select a dataset from a reputable source.
Explore the dataset to understand its structure and content.
Apply data analysis techniques to uncover insights and patterns.
Present your findings in a clear and concise manner.

Contribute to an open-source data science project

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Find an open-source data science project to contribute to, such as a data analysis library or a machine learning algorithm, to enhance your skills and connect with the data science community.

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Identify an open-source data science project that aligns with your interests.
Review the project's documentation and codebase.
Identify areas where you can contribute, such as bug fixes or feature enhancements.
Submit your contributions to the project and engage with the community.

Career center

Learners who complete Learning Python for Data Analysis and Visualization Ver 1 will develop knowledge and skills that may be useful to these careers:

Data Visualization Specialist

A Data Visualization Specialist creates visual representations of data. Python is a popular language for data visualization, and this course will give you a strong foundation in Python programming. You will also learn how to use data visualization tools like matplotlib and seaborn to create clear and concise graphs and charts. This course will help you develop the skills you need to succeed as a Data Visualization Specialist.

See salaries and explore the career path for Data Visualization Specialist

Data Scientist

A Data Scientist uses scientific methods to analyze data and develop models to help businesses solve problems. Python is a popular language for data science, and this course will give you a strong foundation in Python programming. You will also learn how to use data visualization tools like matplotlib and seaborn to create clear and concise graphs and charts. This course will help you develop the skills you need to succeed as a Data Scientist.

See salaries and explore the career path for Data Scientist

Data Analyst

A Data Analyst collects, cleans, and interprets data to help businesses make informed decisions. Python and data visualization are essential skills for a Data Analyst, and this course will provide you with a solid foundation in both areas. You will learn how to use Python to manipulate and analyze data, and how to use data visualization tools like matplotlib and seaborn to create clear and concise graphs and charts. This course will help you develop the skills you need to succeed as a Data Analyst.

See salaries and explore the career path for Data Analyst

Financial Analyst

A Financial Analyst uses data to make investment decisions. Python is a valuable tool for financial analysts, and this course will give you a strong foundation in Python programming. You will also learn how to use data visualization tools like matplotlib and seaborn to create clear and concise graphs and charts. This course will help you develop the skills you need to succeed as a Financial Analyst.

See salaries and explore the career path for Financial Analyst

Business Analyst

A Business Analyst uses data to help businesses make better decisions. Python is a valuable tool for business analysts, and this course will give you a strong foundation in Python programming. You will also learn how to use data visualization tools like matplotlib and seaborn to create clear and concise graphs and charts. This course will help you develop the skills you need to succeed as a Business Analyst.

See salaries and explore the career path for Business Analyst

Operations Research Analyst

An Operations Research Analyst uses data to improve the efficiency of business operations. Python is a valuable tool for operations research analysts, and this course will give you a strong foundation in Python programming. You will also learn how to use data visualization tools like matplotlib and seaborn to create clear and concise graphs and charts. This course will help you develop the skills you need to succeed as an Operations Research Analyst.

See salaries and explore the career path for Operations Research Analyst

Market Researcher

A Market Researcher collects and analyzes data to understand consumer behavior. Python is a valuable tool for market researchers, and this course will give you a strong foundation in Python programming. You will also learn how to use data visualization tools like matplotlib and seaborn to create clear and concise graphs and charts. This course will help you develop the skills you need to succeed as a Market Researcher.

See salaries and explore the career path for Market Researcher

Quantitative Analyst

A Quantitative Analyst uses data to develop financial models. Python is a popular language for quantitative analysts, and this course will give you a strong foundation in Python programming. You will also learn how to use data visualization tools like matplotlib and seaborn to create clear and concise graphs and charts. This course will help you develop the skills you need to succeed as a Quantitative Analyst.

See salaries and explore the career path for Quantitative Analyst

Data Engineer

A Data Engineer builds and maintains data pipelines. Python is a popular language for data engineering, and this course will give you a strong foundation in Python programming. This course may also be helpful if you are interested in a career in data engineering.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

A Machine Learning Engineer develops and deploys machine learning models. Python is a popular language for machine learning, and this course will give you a strong foundation in Python programming. This course may also be helpful if you are interested in a career in machine learning.

See salaries and explore the career path for Machine Learning Engineer

Robotics Engineer

A Robotics Engineer designs, develops, and tests robots. Python is a popular language for robotics, and this course will give you a strong foundation in Python programming. This course may also be helpful if you are interested in a career in robotics.

See salaries and explore the career path for Robotics Engineer

Natural Language Processing Engineer

A Natural Language Processing Engineer develops and deploys natural language processing models. Python is a popular language for natural language processing, and this course will give you a strong foundation in Python programming. This course may also be helpful if you are interested in a career in natural language processing.

See salaries and explore the career path for Natural Language Processing Engineer

Computer Vision Engineer

A Computer Vision Engineer develops and deploys computer vision models. Python is a popular language for computer vision, and this course will give you a strong foundation in Python programming. This course may also be helpful if you are interested in a career in computer vision.

See salaries and explore the career path for Computer Vision Engineer

Software Engineer

A Software Engineer designs, develops, and tests software applications. Python is a popular language for software development, and this course will give you a strong foundation in Python programming. This course may also be helpful if you are interested in a career in software development.

See salaries and explore the career path for Software Engineer

Web Developer

A Web Developer designs and develops websites. Python is a popular language for web development, and this course will give you a strong foundation in Python programming. This course may also be helpful if you are interested in a career in web development.

See salaries and explore the career path for Web Developer