Resources

Discover resources to boost your progress and enhance your data science learning experience and professional performance.

Course Notes

All Course Notes
Course notes are the perfect complementary educational resource in .pdf for anyone who wishes to go in-depth with fundamental to advanced data science concepts and get a taste of our e-learning style.
Gray cover of Backpropagation Algorithm. These course notes are from 365 Data Science.
Course Notes theory

Backpropagation Algorithm

The backpropagation algorithm is the fundamental building block of neural networks and is used to effectively train them through the chain rule method- a technique used to find the derivatives of cost, considering any variable in a nested equation. While most packages already contain backpropagation algorithms in them, knowing the math behind them and how they work will help you better understand more advanced algorithms as well as handle vanilla ones with ease. Check out these free short pdf course notes on the backpropagation algorithm to learn some of the useful formulas and finding the results for backpropagation for the output layer and hidden layer.   

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Gray cover of Neural Network Overview. These course notes are from 365 Data Science.
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Neural Networks Overview

Currently, the closest technology to mimicking the human brain and learning process is deep learning. It uses mathematical functions to map the input to the output and form patterns out of the data. Computationally superior to machine learning, deep learning can even analyze huge sets of unstructured data. At the heart of deep learning are neural networks which mimic the neuron activity in the human brain, enabling us to learn the structure of data by performing various tasks, without the need for human intervention. Check out these short free pdf course notes to find out the three layers of deep neural networks and the activation functions. 

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Gray cover of Intro to Intro to Neural Networks. These course notes are from 365 Data Science.
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Intro to Neural Networks

Machine Learning is the field concerned with building computational  models that can execute high-level tasks using human-like reasoning. In other words, machine learning models possess the ability to learn autonomously. The recent introduction of neural networks has opened a new set of possibilities for machine learning and deep learning. Before you explore them, check out these free pdf course notes on intro to neural networks and get to know the building blocks of a machine learning algorithm, and the two types of supervised learning- regression and classification.

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Grey cover of Probability. These course notes are from 365 Data Science.
Course Notes theory

Probability

We use the intuitive concept of probability on a daily basis in our lives, just by the mere fact that we live in constant uncertainty. Data Science is one of the fields where we need to have conscious mastery and understanding of probability – the backbone of many important data science concepts. If you want to adopt the probabilistic mindset then check out our free pdf course notes which will teach you the basics of probability, combinatorics, Bayesian Notation, discrete distributions, continuous distributions, setting up and solving integrals and expressing complex formulas in Wolfram Alpha. 

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Templates

All Templates
Save hours of browsing through the Internet and accelerate your workflow with code-ready templates for your programming projects. Personally crafted by 365 Data Science instructors, these templates bring a surprising efficiency level to your work process.
Data Science Shortcuts Cheat Sheet
Templates theory

Data Science Shortcuts Cheat Sheet

Discover how to boost your productivity using this data science shortcuts cheat sheet with over 2,000 workarounds in Python IDEs, such as Jupyter, Spyder Rodeo, PyCharm, and Atom, compatible with various operating systems. Amplify your proficiency in R with R Studio shortcuts, streamline MATLAB operations, and manage databases efficiently with SQL shortcuts.     Enhance data visualization in Tableau, easily manage Excel spreadsheets, and conduct statistical analyses seamlessly in SPSS and SAS. This data science shortcuts cheat sheet lets you speed up your everyday tasks while achieving your goals.

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Yellow cover of Multi-Dimensional Dictionaries in Python. This template resource is from 365 Data Science.
Templates python

Multi-Dimensional Dictionaries in Python

The following is a program implementing a multi-dimensional dictionary in Python. The notebook shows how to retrieve keys and values from the dictionary, how to create a new key:value pair and how to loop through the keys and the values using a for-loop. Some other related topics you might be interested in are One-Dimensional Dictionaries in Python, Dictionary Comprehension in Python, Using Counter - a Dictionary Subclass in Python. The Multi-Dimensional Dictionaries in Python free template is among the topics covered in detail in the 365 Program. 

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Yellow cover of Methods in Python - Functions Inside Classes in Python. This template resource is from 365 Data Science.
Templates python

Methods in Python - Functions Inside Classes in Python

In Python, we can design and create our own objects with the help of classes. In this free notebook, we will design a class and define two functions inside - two methods. In Python, methods are accessed through the dot-notation. They help interact with an object and are an essential part of a class. Some other related topics you might be interested in are Defining classes in Python, The Pass-Statement in Python, Creating a Constructor in Python - the INIT method, Class Variables in Python, Inheritance in Python. The Methods in Python – Functions Inside Classes in Python template is among the topics covered in detail in the 365 Program.

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Yellow cover of Inheritance in Python. This template resource is from 365 Data Science.
Templates python

Inheritance in Python

In Python, we can design and create our own objects. This is done with the help of classes. The design of these (parent) classes can be inherited by other classes. This allows classes to make use of the constructor and the methods of the parent class. In this notebook, we demonstrate how this can be done with a thorough example. Some other related topics you might  be interested in are Defining classes in Python, The pass-statement in Python, Creating a constructor in Python - the INIT method, Class variables in Python, Methods in Python - functions inside classes. The Inheritance in Python template is among the topics covered in detail in the 365 Program. 

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Infographics

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Navigate your way through the sea of weighty data science content with the help of our 365 Data Science infographics and make your learning experience much simpler and more memorable.
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Linear Regression Infographic

This Linear Regression infographic demystifies the principles behind a standard statistical model used in machine learning—showing how to predict and understand linear variable relationships. It depicts its mathematical formula, training process, and practical applications with examples. Are you struggling to recall the linear regression assumptions? Unsure when to apply linear regression in machine learning? Download our infographic for an instant cheat sheet.

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Infographics artificial intelligence

How to Prompt ChatGPT Effectively

ChatGPT is a powerhouse AI algorithm transforming how we lead, work, and brainstorm. By typing our desired output as a prompt into ChatGPT, the generative AI model returns an actionable, informed response that meets your needs.   Accelerate your productivity by learning how to interact with this indispensable tool. Our How to Prompt ChatGPT Effectively infographic is a structured resource that guides you in creating effective prompts for ChatGPT.   Construct practical prompts that generate insightful responses and inspire creative solutions. To boost your productivity and stay current, you must take advantage of the best tools at your disposal. So, start engaging with ChatGPT like a pro and future-proof your skills. 

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Infographics artificial intelligence

When, What, Why of AI

Artificial intelligence is becoming a household discussion, yet it’s still widely misunderstood. Our When, What, Why of AI infographic aims to demystify the concept by answering the most popular questions: What is artificial intelligence? How does it work? Who invented AI? Who uses AI models?  We’ve divided the AI infographic into two separate categories in terms of methodology: rule-based and statistical. Learn what АI concepts like deep learning, NLP, and computer vision mean and when they were first popularized. You’ll also discover what models they’re based on and the main AI applications. Finally, we introduce AI pioneers whose contributions have shaped—and continue to shape—the tech-advancement landscape. 

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Infographics artificial intelligence

AI Ethics Consideration

As deep learning and artificial intelligence rapidly evolve, it’s essential to consider how their development affects the broader community. In other words, we shouldn’t ignore the ethics of AI and its implications.  With this informative AI Ethics Considerations infographic, we look at the ethics in artificial intelligence to answer the question, “Is AI actually ethical?” By examining scenarios like copyrighted materials and biased data through the AI lens, we present potential ethical issues for companies and end users.  This resource aims to create a broader conversation about the development of a more responsible and ethical use of AI models. Artificial intelligence will continue to shape our future, and we should harness the transformative power that automatization brings us. We also present a list of potential remedies to facilitate a more considerate approach that caters to the broader human experience and creates more ethical AI models. 

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Career Guides

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Save yourself hours of browsing the internet and reading through fragmented pieces of outdated information about the data science industry with our career guides—your roadmap to designing your professional development.
How to Learn AI. A Beginner's Guide
Career Guides artificial intelligence

How to Learn AI. A Beginner's Guide

Recent technological developments have spurred both excitement about the world of opportunities and fear of becoming obsolete. While the adoption of artificial intelligence has led to the automation of many tasks, new roles continue to emerge daily. Upskilling is the only way to stay current in this AI-driven world, and those who know how to adapt and leverage new technologies will thrive in the future job market. Our comprehensive How to Learn AI guide helps you navigate the dynamic work environment by introducing you to a future-proof strategy for getting started with AI.

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Career Guides

Data Analyst Career Guide

Understanding and interpreting data has become more crucial as we progress into the digital age. Data analysts use their skills to analyze complex datasets and provide valuable insights that drive informed decision-making and promote business growth. Our data analyst career guide explores what it takes to become a successful data analyst, including the role description, necessary qualifications and skills, and the data analyst job outlook for 2023. The true value of the guide is in its extensive section concerning your application process from resume to interview. You’ll learn how to structure your resume, write a winning cover letter, and provide exceptional answers to data analyst interview questions.

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Career Guides

Data Analyst Resume Template

A winning data analyst resume must be brief, easy to scan, mistake-free, and tailored to a particular job ad. But building one from scratch can be time-consuming. Our free data analyst resume template is the perfect resource to slash formatting time and allow for quick customization.

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Career Guides

Data Analyst Cover Letter Template

Crafting an effective data analyst cover letter begins with skimming through a massive dataset: your experience. Demonstrate your value to the hiring manager by crafting a compelling story about your skills and experience. Our free data analyst cover letter template allows you to use a tried-and-tested method for impressing employers.

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Practice Exams

All Practice Exams
A selection of practice exams that will test your current data science knowledge. Identify key areas of improvement to strengthen your theoretical preparation, critical thinking, and practical problem-solving skills so you can get one step closer to realizing your professional goals.
Green cover of Excel Mechanics. This practice exam is from 365 Data Science.
Practice Exams excel

Excel Mechanics

Imagine if you had to apply the same Excel formatting adjustment to both Sheet 1 and Sheet 2 (i.e., adjust font, adjust fill color of the sheets, add a couple of empty rows here and there) which contain thousands of rows. That would cost an unjustifiable amount of time. That is where advanced Excel skills come in handy as they optimize your data cleaning, formatting and analysis process and shortcut your way to a job well-done. Therefore, asses your Excel data manipulation skills with this free practice exam.  

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Green cover of Formatting Excel Spreadsheets. This practice exam is from 365 Data Science.
Practice Exams excel

Formatting Excel Spreadsheets

Did you know that more than 1 in 8 people on the planet uses Excel and that Office users typically spend a third of their time in Excel. But how many of them use the popular spreadsheet tool efficiently? Find out where you stand in your Excel skills with this free practice exam where you are a first-year investment banking analyst at one of the top-tier banks in the world. The dynamic nature of your position will test your skills in quick Excel formatting and various Excel shortcuts 

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Green cover of Hypothesis Testing. This practice exam is from 365 Data Science.
Practice Exams excel

Hypothesis Testing

Whenever we need to verify the results of a test or experiment we turn to hypothesis testing. In this free practice exam you are a data analyst at an electric car manufacturer, selling vehicles in the US and Canada. Currently the company offers two car models – Apollo and SpeedX.  You will need to download a free Excel file containing the car sales of the two models over the last 3 years in order find out interesting insights and  test your skills in hypothesis testing. 

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Green cover of Confidence Intervals. This practice exam is from 365 Data Science.
Practice Exams excel

Confidence Intervals

Confidence Intervals refers to the probability of a population parameter falling between a range of certain values. In this free practice exam, you lead the research team at a portfolio management company with over $50 billion dollars in total assets under management. You are asked to compare the performance of 3 funds with similar investment strategies  and are given a table with the return of the three portfolios over the last 3 years. You will have to use the data to answer questions that will test your knowledge in confidence intervals. 

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