Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this practical guide-now including examples in Python as well as R-explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data scientists use statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages, and have had some exposure to statistics but want to learn more, this quick reference bridges the gap in an accessible, readable format. With this updated edition, you'll dive into: Exploratory data analysis Data and sampling distributions Statistical experiments and significance testing Regression and prediction Classification Statistical machine learning Unsupervised learning.

There's a lot of discussion about what we can do with data but precious little about what we should or shouldn't do with data. Learn more with these top data ethics books.

65 free data science resources we've hand-picked and annotated for beginners. Learn programming, business analytics, machine learning, and more.

GitHub has awesome collection of data science resources. This article provides this list of best Data Science Tutorials & Data Scientists To Follow on GitHub.

Here's a list of some Great Python courses for anybody wanting to learn Python for data science.

A handy Pandas Cheat Sheet useful for the aspiring data scientists and contains ready-to-use codes for data wrangling. The cheat sheet summarize the most commonly used Pandas features and APIs. This cheat sheet will act as a crash course for Pandas beginners and help you with various fundamentals of Data Science. It can be used by experienced users as a quick reference. * Pandas API Reference * Pandas User Guide * Data Wrangling with Pandas Cheat Sheet Pandas setup Pandas is open s

List of 25 best machine learning and data science github repositories from 2018 with projects divided into different categories.

Today, we’re going to look at 5 popular clustering algorithms that data scientists need to know and their pros and cons!

There are lots of books for getting started with Python, so where should you start? In this blog post, we bring you our list of the best FREE Python books for Data Science we've found.

Discover Your Genetic Blueprint and Uniqueness! Engage your budding scientists in an exciting exploration of inherited traits with these versatile resources! Whether utilized as engaging worksheets or integrated into students' science journals, these handouts offer a hands-on experience for practic...

Here's a list of some Great Python courses for anybody wanting to learn Python for data science.

Explore the world of Data Science with these FREE Data Science Books. In this blog post, you'll find a curated list of FREE ebooks on Data Science every Data Scientist should read. Check them out!

Why do Data Scientists think that stats is dead? Where does the notion that there is no longer any need for statistical analysis come from? And are they right?

Getting started with R can be difficult, but it doesn't have to be. In this blog post (series) I show you the very first steps to learning R with confidence.

Here's a list of some Great Python courses for anybody wanting to learn Python for data science.

If you want to be an expert data scientist you're going to need a strong grounding in statistics, programming, AI and more. These courses will help you.

Check out some of the top data science courses at Udemy.

You may know SQL basics, but are you taking advantage of its expressive power? This second edition applies a highly practical approach to Structured Query Language (SQL) so you can create and manipulate large stores of data. Based on real-world examples, this updated cookbook provides a framework to help you construct solutions and executable examples in several flavors of SQL, including Oracle, DB2, SQL Server, MySQL, and PostgreSQL. SQL programmers, analysts, data scientists, database administrators, and even relatively casual SQL users will find SQL Cookbook to be a valuable problem-solving guide for everyday issues. No other resource offers recipes in this unique format to help you tackle nagging day-to-day conundrums with SQL. The second edition includes: Fully revised recipes that recognize the greater adoption of window functions in SQL implementations Additional recipes that reflect the widespread adoption of common table expressions (CTEs) for more readable, easier-to-implement solutions New recipes to make SQL more useful for people who aren't database experts, including data scientists Expanded solutions for working with numbers and strings Up-to-date SQL recipes throughout the book to guide you through the basics

The use of Python as a data science tool has been on the rise over the past few years: 54% of the respondents of the latest O’Reilly Data Science Salary Survey indicated that they used Python. The results of the 2015 survey indicated that 51% of the respondents used Python. Nobody can deny that Python has been on… Read More »[Cheat Sheet] Python Basics For Data Science

In this blog post, we walk through the 5 steps that one would have to take to become a data scientist!

Explore the world of Data Science with these FREE Data Science Books. In this blog post, you'll find a curated list of FREE ebooks on Data Science every Data Scientist should read. Check them out!

What is data? Why is it so important? And What can we do with it? Check out this blog post for 12 tips on what you can do with your data!

Explore the world of Data Science with these FREE Data Science Books. In this blog post, you'll find a curated list of FREE ebooks on Data Science every Data Scientist should read. Check them out!

Whatever you plan to do with your data, your first step is to get organised. Here are 7 secrets of data handling that will get you a great start...

Explore the world of Data Science with these FREE Data Science Books. In this blog post, you'll find a curated list of FREE ebooks on Data Science every Data Scientist should read. Check them out!

Explore the world of Data Science with these FREE Data Science Books. In this blog post, you'll find a curated list of FREE ebooks on Data Science every Data Scientist should read. Check them out!

If you're making the switch to Data Science, you need to update your Statistics knowledge. Check out the best Statistics Books for Beginner Data Scientist.

This 'TensorFlow for Beginners Cheat Sheet' is your comprehensive digital guide to diving deep into TensorFlow and its powerful capabilities! Spanning 7 pages, this downloadable PDF is brimming with vital insights, covering TensorFlow Basics, Deep Learning Architectures, Neural Network Training Techniques, TensorFlow 2.x Features, Keras Integration, Tensor Manipulations, Data Handling with tf.data, Optimization Strategies, and much more. Perfect for budding data scientists, AI practitioners, students, and professionals aiming to elevate their TensorFlow proficiency. Get a panoramic view of TensorFlow's rich ecosystem and tools. You're a beginner in Python? No problem, I've got you covered: https://www.etsy.com/de/listing/1496204311/python-for-beginners-cheat-sheet-program?ref=listings_manager_grid Disclaimer: This is a digital product!

Getting little learners excited about science is easy with engaging experiments and thematic units. Teaching them to collect and organize data like scientists is accomplished with a Science Notebook.Here are 3 reasons why using a Science Notebook with your learners can help your classroom and curriculum. 1) Work Doesn't Get Thrown AwayWhether you are homeschooling or in the

Different Types of Probability Distribution (Characteristics & Examples)

Weather Science Project Choice Menu - Global and Local, Severe, Weather Forecasting & Phenomenon includes great interactive resources! Students choose from a matrix of 6 Topics x 6 Products. There are a total of 36 different combinations! Topics include: exploring extreme and rare weather phenomena, storms such as hurricanes and tornadoes, and understanding how scientists gather data and predict weather. I am "forecasting" your students will love this weather project! Under each topic are several sub-topics & resources creating great flexibility for this project menu! Weather affects our lives daily, but many students have not been captivated by it yet. Give them the opportunity to explore different aspects of weather and its effects. What is included: Includes a teacher presentation (25 slides) with project choice menu, instructions, interactive resources, project products ideas and resources, rubric & teacher resources. A 17 slide student research version is provided as well. Student document pages guide organization & keep students on track (3 student pages). Finally, a teacher resource document (5 pages) is provided for all the topics and products in the menu. Objective: Weather affects our lives daily, but many students have not been captivated by it yet. This project will peak student’s interest by giving them the opportunity to explore different aspects of weather and its effects. Topics include: exploring extreme and rare weather phenomena, storms such as hurricanes and tornadoes, and understanding how scientists gather data and predict weather. Once students research their topic, they then create a product of their choice to showcase their research and knowledge. Science Concepts: weather formation, weather forecasting, ocean and hydrosphere’s role in storm formation, local and global weather, el niño and la niña, jet stream, weather forecasting and the science of meteorology IB Connections and Skills: This matches well with Criterion D - Reflecting on the Impacts of Science. Skills: Communication: Language skills - find information for disciplinary and interdisciplinary inquiries, using a variety of media; Research Skills: Make connections between various sources of information Lesson Structure and Teacher Tips: This project makes a great end of the year project or a cumulative project at the end of a unit. Or this can be used to inspire students to complete further self-directed research. This project will require several days in class. Keep in mind what requirements are your end goal for students in order to assess the projects. The lesson includes a teacher presentation with a grading rubric, teacher resources document, student interactive slides, and digital student pages for organization and keeping students on track. Standards it relates to: 8.10(B) identify how global patterns of atmospheric movement influence local weather using weather maps that show high and low pressures and fronts 8.10(C) identify the role of the oceans in the formation of weather systems such as hurricanes NGSS: MS-ESS2-5. Collect data to provide evidence for how the motions and complex interactions of air masses result in changes in weather conditions. Your business is greatly appreciated! Copyright © Cognitive Treks. All rights reserved by author.

Explore the world of Data Science with these FREE Data Science Books. In this blog post, you'll find a curated list of FREE ebooks on Data Science every Data Scientist should read. Check them out!

Explore the world of Data Science with these FREE Data Science Books. In this blog post, you'll find a curated list of FREE ebooks on Data Science every Data Scientist should read. Check them out!

Statistical Hypothesis Testing - just 4 hypothesis testing steps and a statistical test flow chart will help you choose the correct statistical test

If you're making the switch to Data Science, you need to update your Statistics knowledge. Check out the best Statistics Books for Beginner Data Scientist.

Explore the world of Data Science with these FREE Data Science Books. In this blog post, you'll find a curated list of FREE ebooks on Data Science every Data Scientist should read. Check them out!

A walkthrough of the Udemy dashboard that got me a job offer from one of the biggest names in academic publishing.

You wouldn’t start building your house without putting the foundations in place, would you? Read this blog post to discover the 3 crucial steps you need to take before you start analysing your data.