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Data Analysis Using Python

This course provides an introduction to basic data science techniques using Python. Students are introduced to core concepts like Data Frames and joining data, and learn how to use data analysis libraries like pandas, numpy, and matplotlib. This course provides an overview of loading, inspecting, and querying real-world data, and how to answer basic questions about that data. Students will gain skills in data aggregation and summarization, as well as basic data visualization.

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Syllabus

Module 1 : Loading, Querying, & Filtering Data Using the csv Module

This first module provides students with an overview of loading, inspecting, and exploring data using Python's simple csv library. To get started, this module includes a brief overview of Jupyter Notebook and a concise review of basic Python, including data structures, loops, and functions. This module showcases to the students an in-depth analysis of data stored in a .csv file, including basic querying, approaches for dealing with data errors, and how to filter and sort data based on a variety of criteria.

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Provides hands-on experience with data analysis tools like pandas, numpy, and matplotlib, which is standard practice in industry

Develops a strong foundation in core data science techniques and concepts for novices

Builds skills in data aggregation, summarization, and visualization, which are highly relevant to data analysis

Taught by instructors like Brandon Krakowsky who are recognized for their expertise in data science

Examines real-world data analysis through examples and exercises

Advisable to have basic Python knowledge before beginning this course

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Reviews summary

Foundational python data analysis

According to learners, this course offers a well-structured and solid introduction to Data Analysis Using Python. Students frequently praise the clear explanations from the instructor and the hands-on labs and practical exercises, which include real-world data cleaning and even building a simple recommendation system. It's described as a great starting point for understanding core libraries like pandas, numpy, and matplotlib. However, some learners note that while it provides an excellent foundation, it may feel too basic for intermediate learners and the initial Python review might be superficial for absolute programming novices. Forum support and dataset variety were also areas mentioned for potential improvement.

Ideal for beginners to intermediate users seeking a foundational overview.

"A solid introduction to data analysis... It's a great starting point, but don't expect to become an expert overnight."

"The course covers the basics... Good for absolute beginners, but not much for intermediate learners."

"I found this course somewhat basic for my needs. It feels more like a quick overview than an in-depth dive."

The instructor's explanations are clear, concise, and easy to follow.

"The instructor's explanations were spot on and easy to follow. Highly recommend for beginners!"

"The instructor was clear, but the forum support could be improved."

"The explanations are clear, and the practical application of pandas and matplotlib is excellent."

Emphasizes practical application through labs, exercises, and real-world examples.

"The pandas and numpy modules were explained clearly, and the hands-on labs were very helpful. I particularly appreciated the practical examples for cleaning data and handling missing values."

"The exercises were engaging and reinforced the concepts well."

"The section on building a simple recommendation system was a pleasant surprise and very practical."

"Hands down one of the best introductory courses for data analysis. The practical application of pandas and matplotlib is excellent."

Provides a solid, well-structured introduction to data analysis.

"This course is incredibly well-structured and provides a fantastic foundation for anyone looking to get into data analysis with Python."

"Excellent course! The material is presented logically, building from basic CSV handling to more advanced pandas operations."

"A solid foundation. I particularly liked the hands-on coding aspect and the explanations of `DataFrames`."

Some suggestions for enhanced forum support and diverse datasets.

"The instructor was clear, but the forum support could be improved. I had a question that went unanswered for a few days."

"I also wish there were more diverse datasets to work with; the examples felt a bit repetitive after a while."

Pace might be challenging for those with no prior programming experience.

"If you're completely new to programming, you might struggle with the pace."

"The initial Python review was too superficial for true beginners, and the more advanced topics like joining data were not elaborated enough."

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 Data Analysis Using Python with these activities:

Review previous math concepts related to data science

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Enhance your understanding of data science by refreshing your knowledge of relevant mathematical concepts.

Browse courses on Statistics

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Review online resources or textbooks on statistics and linear algebra.
Focus on concepts such as probability, distributions, and matrix operations.

Refresh knowledge of programming fundamentals

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Review basic programming concepts such as data types, control flow, and functions to strengthen your foundation for data science.

Browse courses on Python

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Review online tutorials or textbooks on Python basics.
Complete practice exercises or code challenges to reinforce your understanding.

Explore a book on data science

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Gain insights from experts by reading a book specifically dedicated to data analysis using Python.

View Python for Data Analysis on Amazon

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Read selected chapters or sections relevant to the course material.
Take notes or summarize key concepts to enhance comprehension.

Ten other activities

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Review of Basic Python Concepts

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Review basic Python concepts to strengthen your foundation for data science.

Browse courses on Python Basics

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Revisit data structures (e.g., lists, dictionaries).
Practice using loops and functions.

Join a study group or online forum for data science

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Engage with peers, share knowledge, and get support by actively participating in study groups or online forums.

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Find or create a study group with fellow students or individuals interested in data science.
Set regular meeting times to discuss course material, share resources, and work on problems together.
Be an active participant by contributing ideas, asking questions, and providing support.

Practice Loading and Querying Data

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Practice loading and querying data to improve your understanding of Python's csv library and basic data analysis techniques.

Browse courses on Loading Data

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Load a CSV file into a DataFrame.
Query the DataFrame using basic operators (e.g., ==, !=, >, <).
Filter the DataFrame based on specific criteria.
Sort the DataFrame by one or more columns.

Tutorial on Pandas for Data Manipulation

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Follow a tutorial to enhance your skills in data manipulation using the pandas library.

Browse courses on Data Manipulation

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Follow a guided tutorial on using pandas for data manipulation.
Apply the techniques learned in the tutorial to your own data analysis project.

Solve data analysis practice problems

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Strengthen your problem-solving skills and apply course concepts by working through practice problems.

Browse courses on Data Manipulation

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Find online resources or textbooks with data analysis practice problems.
Solve problems independently, focusing on understanding the approach and implementation.
Review solutions or consult with peers to verify your understanding.

Exercises on Data Aggregation and Summarization

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Solve exercises to strengthen your skills in data aggregation and summarization.

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Group data by one or more columns.
Calculate summary statistics (e.g., mean, median, standard deviation).
Create pivot tables to summarize data.
Visualize the summarized data using histograms or scatterplots.

Follow online tutorials on specific data science techniques

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Expand your knowledge and explore specific techniques by following guided tutorials that provide step-by-step instructions.

Browse courses on Data Cleaning

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Identify specific areas or techniques you want to enhance.
Find reputable online tutorials or courses that align with your learning goals.
Follow the tutorials carefully, taking notes and experimenting with the code.

Data Visualization Project

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Create a data visualization project to demonstrate your proficiency in data analysis and visualization.

Browse courses on Data Visualization

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Collect and clean a dataset.
Explore the data and identify trends or patterns.
Choose appropriate visualizations to represent the data.
Create visualizations using Matplotlib.
Present your findings in a clear and concise manner.

Develop a mini data analysis project

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Apply your skills to a practical project, reinforcing your understanding of the data analysis process.

Browse courses on Data Visualization

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Define a small-scale data analysis project that interests you.
Gather and explore the necessary data.
Analyze the data, draw insights, and prepare visualizations.
Present your findings in a clear and concise manner.

Become a mentor or tutor for junior data science learners

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Reinforce your understanding by sharing your knowledge and guiding others in their data science journey.

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Offer your services as a mentor or tutor to students or individuals who are new to data science.
Share your knowledge, provide guidance, and answer questions to support their learning.
Reflect on your own understanding as you explain concepts and assist others.

Career center

Learners who complete Data Analysis Using Python will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts analyze and interpret data to help businesses make informed decisions. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use their knowledge of data analysis and machine learning to solve business problems. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the programming skills you need to build machine learning models.

See salaries and explore the career path for Data Scientist

Statistician

Statisticians use their knowledge of statistics to collect, analyze, and interpret data. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Statistician

Market Researcher

Market Researchers use their knowledge of data analysis to understand consumer behavior. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Market Researcher

Data Engineer

Data Engineers design and build the systems that store and process data. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the programming skills you need to build data pipelines.

See salaries and explore the career path for Data Engineer

Financial Analyst

Financial Analysts use their knowledge of data analysis to evaluate investments. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Financial Analyst

Business Analyst

Business Analysts use their knowledge of data analysis to help businesses improve their operations. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Business Analyst

Data Visualization Analyst

Data Visualization Analysts use their knowledge of data analysis to create visual representations of data. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Data Visualization Analyst

Operations Research Analyst

Operations Research Analysts use their knowledge of data analysis to optimize business processes. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Operations Research Analyst

Data Journalist

Data Journalists use their knowledge of data analysis to tell stories with data. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the writing skills you need to create clear and concise stories.

See salaries and explore the career path for Data Journalist

Social Media Analyst

Social Media Analysts use their knowledge of data analysis to track and measure the effectiveness of social media campaigns. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Social Media Analyst

Software Tester

Software Testers use their knowledge of data analysis to find and fix bugs in software. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Software Tester

Technical Writer

Technical Writers use their knowledge of data analysis to create documentation for software and other products. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the writing skills you need to create clear and concise documentation.

See salaries and explore the career path for Technical Writer

Quality Assurance Analyst

Quality Assurance Analysts use their knowledge of data analysis to ensure that products and services meet quality standards. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Quality Assurance Analyst

Web Analyst

Web Analysts use their knowledge of data analysis to track and measure the effectiveness of websites. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques. You will learn how to load, clean, and manipulate data, as well as how to summarize and visualize data. This course will also help you develop the critical thinking skills you need to identify trends and patterns in data.

See salaries and explore the career path for Web Analyst

Reading list

We've selected 15 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Analysis Using Python.

Probabilistic Machine Learning

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Provides a comprehensive introduction to machine learning from a probabilistic perspective. It covers the basics of supervised and unsupervised learning, as well as more advanced topics.

Probabilistic Machine Learning: Advanced Topics...

Hardcover

$$$$

Machine Learning Q and AI

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Provides a comprehensive introduction to machine learning using Python. It covers the basics of supervised and unsupervised learning, as well as more advanced topics.

Data Analysis Using Python

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What's inside

Syllabus

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Reviews summary

Foundational python data analysis

Activities

Career center

Reading list

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