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Data Analysis

14 resources

Level
Type

📹Videos(3)

video👁️ 0

Data Analysis with Python and Pandas Tutorial

Corey Schafer tutorial highly recommended in r/datascience

beginner🇬🇧
video👁️ 0

Excel for Beginners - The Complete Course

Highly recommended Excel basics for data analysis

beginner🇬🇧
video👁️ 0

Data Analysis with Python - Full Course for Beginners (Numpy, Pandas, Matplotlib, Seaborn)

Comprehensive free course from freeCodeCamp

beginner🇬🇧

🎓Courses(5)

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course👁️ 0

SQL for Data Science

As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimize their businesses. This is a data scientist, “part mathematician, part computer scientist, and part trend spotter” (SAS Institute, Inc.). According to Glassdoor, being a data scientist is the best job in America; with a median base salary of $110,000 and thousands of job openings at a time. The skills necessary to be a good data scientist include being able to retrieve and work with data, and to do that you need to be well versed in SQL, the standard language for communicating with database systems. This course is designed to give you a primer in the fundamentals of SQL and working with data so that you can begin analyzing it for data science purposes. You will begin to ask the right questions and come up with good answers to deliver valuable insights for your organization. This course starts with the basics and assumes you do not have any knowledge or skills in SQL. It will build on that foundation and gradually have you write both simple and complex queries to help you select data from tables. You'll start to work with different types of data like strings and numbers and discuss methods to filter and pare down your results. You will create new tables and be able to move data into them. You will learn common operators and how to combine the data. You will use case statements and concepts like data governance and profiling. You will discuss topics on data, and practice using real-world programming assignments. You will interpret the structure, meaning, and relationships in source data and use SQL as a professional to shape your data for targeted analysis purposes. Although we do not have any specific prerequisites or software requirements to take this course, a simple text editor is recommended for the final project. So what are you waiting for? This is your first step in landing a job in the best occupation in the US and soon the world!

beginner🇬🇧
course👁️ 0

Data Analysis with Python

Analyzing data with Python is a key skill for aspiring Data Scientists and Analysts! This course takes you from the basics of importing and cleaning data to building and evaluating predictive models. You’ll learn how to collect data from various sources, wrangle and format it, perform exploratory data analysis (EDA), and create effective visualizations. As you progress, you’ll build linear, multiple, and polynomial regression models, construct data pipelines, and refine your models for better accuracy. Through hands-on labs and projects, you’ll gain practical experience using popular Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, SciPy, and Scikit-learn. These tools will help you manipulate data, create insights, and make predictions. By completing this course, you’ll not only develop strong data analysis skills but also earn a Coursera certificate and an IBM digital badge to showcase your achievement.

intermediate🇬🇧
course👁️ 0

Data Analysis with R Programming

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data.

beginner🇬🇧
course👁️ 0

Data Analysis with Python

Learn data analysis with Python! Master Pandas, NumPy, and more with this free course from freeCodeCamp.org.

beginner🇬🇧
course👁️ 0

Data Analysis with Python

Analyzing data with Python is a key skill for aspiring Data Scientists and Analysts! This course takes you from the basics of importing and cleaning data to building and evaluating predictive models. You’ll learn how to collect data from various sources, wrangle and format it, perform exploratory data analysis (EDA), and create effective visualizations. As you progress, you’ll build linear, multiple, and polynomial regression models, construct data pipelines, and refine your models for better accuracy. Through hands-on labs and projects, you’ll gain practical experience using popular Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, SciPy, and Scikit-learn. These tools will help you manipulate data, create insights, and make predictions. By completing this course, you’ll not only develop strong data analysis skills but also earn a Coursera certificate and an IBM digital badge to showcase your achievement.

beginner🇬🇧

🌐Websites(5)

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website👁️ 0

Towards Data Science

Articles and tutorials on data analysis techniques

beginner🇬🇧
website👁️ 0

Towards Data Science

Articles and tutorials on Medium for data analysis practitioners

beginner🇬🇧
website👁️ 0

DataQuest

Interactive data analysis courses, free tier available

beginner🇬🇧
website👁️ 0

datacamp.com

DataCamp is an online learning platform for data science and analytics, offering interactive, browser-based courses in Python, R, SQL, and more, with hands-on exercises, projects, and skill tracks to build practical data analysis skills.

intermediate🇬🇧
website👁️ 0

towardsdatascience.com

Towards Data Science is a popular publication offering practical tutorials, explainers, and case studies on data science, analytics, and AI. It features hands-on articles with code in Python, R, and SQL, covering data analysis techniques, visualization, machine learning, and career guidance from practitioners.

intermediate🇬🇧

🎙️Podcasts(1)

podcast👁️ 0

The Data Science Podcast

Produced by UC Berkeley's Data Science Undergraduate Studies. In this space, you will hear from a variety of distinguished Data Science educators and professionals. The individuals we’ll speak with are diverse in experience and perspective, but share the common goal of shaping the future of Data Science Education! Transcripts available at https://datascienceeducation.substack.com/ To learn more about UC Berkeley's Data Science Undergraduate Studies, visit our website at https://cdss.berkeley.edu/dsus. datascienceeducation.substack.com

beginner🌐

Frequently Asked Questions

What are the best free resources to learn Data Analysis?

Dantes has curated 32 resources for Data Analysis, including 8 videos, 4 courses, 5 websites. All resources are hand-picked for quality — no algorithmic filler. Browse the full list above to find the format that works best for you.

Is Data Analysis hard to learn?

Data Analysis is approachable at the beginner level — there are resources here specifically for those starting from scratch. As you progress, intermediate and advanced material is also available to take your skills further.

What types of Data Analysis learning resources are available on Dantes?

For Data Analysis, Dantes has curated 8 videos, 4 courses, 5 websites. Each resource type serves a different learning style: videos and YouTube for visual learners, books for depth, courses for structured progression, and websites for quick reference.

How does Dantes select Data Analysis resources?

Dantes is an algorithm-free learning directory. Resources are hand-curated based on quality, accuracy, and usefulness — not engagement metrics or paid placements. The goal is to surface the best learning material for Data Analysis, whether it's a free YouTube series, a classic textbook, or an open courseware from a top university.

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