Resources
Discover resources to boost your progress and enhance your data science learning experience and professional performance.Course Notes
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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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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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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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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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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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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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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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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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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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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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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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ABCs of AI and Deep Learning
Artificial intelligence is a trending topic that intrigues and perplexes. But what is it, and how does it work? Our comprehensive ABCs of AI and Deep Learning Infographic introduces you to the basics of artificial intelligence through its deep learning foundations. Arranged alphabetically, this glossary provides an overview of essential terms and phrases that define deep learning and AI concepts. Each letter of the alphabet represents methodologies, such as convolutional neural networks, natural language processing, and Xavier initialization. Use the ABCs of AI and Deep Learning Infographic to foster your curiosity and navigate the complexities of these transformative technologies.
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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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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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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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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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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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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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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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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.
Learn MoreCheck out our most helpful downloadable resources according to 365 Data Science students and our expert team of instructors.
Introduction to Data Science Disciplines
The term “Data Science” dates back to the 1960s, to describe the emerging field of working with large amounts of data that drives organizational growth and decision-making. While the essence has remained the same, the data science disciplines have changed a lot over the past decades thanks to rapid technological advancements. In this free introduction to data science practice exam, you will test your understanding of the modern day data science disciplines and their role within an organization.
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Excel Basics
Ever since its first release in 1985, Excel continues to be the most popular spreadsheet application to this day- with approximately 750 million users worldwide, thanks to its flexibility and ease of use. No matter if you are a data scientist or not, knowing how to use Excel will greatly improve and optimize your workflow. Therefore, in this free Excel Basics practice exam you are going to work with a dataset of a company in the Fast Moving Consumer Goods Sector as an aspiring data analyst and test your knowledge on basic Excel functions and shortcuts.
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Intrо to Machine Learning
State-of-the-art machine learning algorithms have opened a whole new realm of possibilities for businesses to optimize their processes and create new product/service features, that maximize competitive advantages. Used in recommendation systems, fraud detection, spam filtering, self-driving cars, to name a few, these advanced algorithms are only getting more popular by the day. Take this free machine learning practice exam and test your knowledge on supervised, unsupervised and reinforcement machine learning, and their applications.
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Useful Tools in Excel
What Excel lacks in data visualization tools compared to Tableau, or computational power for analyzing big data compared to Python, it compensates with accessibility and flexibility. Excel allows you to quickly organize, visualize and perform mathematical functions on a set of data, without the need for any programming or statistical skills. Therefore, it is in your best interest to learn how to use the various Excel tools at your disposal. This practice exam is a good opportunity to test your excel knowledge in the text to column functions, excel macros, row manipulation and basic math formulas.
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Fundamentals of Descriptive Statistics
Descriptive statistics helps us understand the actual characteristics of a dataset by generating summaries about data samples. The most popular types of descriptive statistics are measures of center: median, mode and mean. In this free practice exam you have been appointed as a Junior Data Analyst at a property developer company in the US, where you are asked to evaluate the renting prices in 9 key states. You will work with a free excel dataset file that contains the rental prices and houses over the last years.
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Excel Functions
The majority of data comes in spreadsheet format, making Excel the #1 tool of choice for professional data analysts. The ability to work effectively and efficiently in Excel is highly desirable for any data practitioner who is looking to bring value to a company. As a matter of fact, being proficient in Excel has become the new standard, as 82% of middle-skill jobs require competent use of the productivity software. Take this free Excel Functions practice exam and test your knowledge on removing duplicate values, transferring data from one sheet to another, rand using the VLOOKUP and SUMIF function.
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Fundamentals of Inferential Statistics
While descriptive statistics helps us describe and summarize a dataset, inferential statistics allows us to make predictions based off data. In this free practice exam, you are a data analyst at a leading statistical research company. Much of your daily work relates to understanding data structures and processes, as well as applying analytical theory to real-world problems on large and dynamic datasets. You will be given an excel dataset and will be tested on normal distribution, standardizing a dataset, the Central Limit Theorem among other inferential statistics questions.
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SQL SELECT Statement
SQL is one of the most popular and in-demand programming languages, because of its intuitive syntax, ubiquitous presence in the business world, and ability to query data and perform analysis. Therefore, possessing SQL skills will give you a significant career advantage in the modern data-driven workforce. Test your knowledge in the basics of SQL with this free SQL SELECT Statement practice exam designed by 365 Data Science instructor Martin Ganchev. These set of SQL questions will test your knowledge on creating databases, SQL Constraints, and the SQL Select Query by giving you a free .sql file containing company data, to work with.
Learn MoreMost Popular Resources
Check out our most helpful downloadable resources according to 365 Data Science students and our expert team of instructors.
Introduction to Data Science Disciplines
The term “Data Science” dates back to the 1960s, to describe the emerging field of working with large amounts of data that drives organizational growth and decision-making. While the essence has remained the same, the data science disciplines have changed a lot over the past decades thanks to rapid technological advancements. In this free introduction to data science practice exam, you will test your understanding of the modern day data science disciplines and their role within an organization.
Learn MoreExcel Basics
Ever since its first release in 1985, Excel continues to be the most popular spreadsheet application to this day- with approximately 750 million users worldwide, thanks to its flexibility and ease of use. No matter if you are a data scientist or not, knowing how to use Excel will greatly improve and optimize your workflow. Therefore, in this free Excel Basics practice exam you are going to work with a dataset of a company in the Fast Moving Consumer Goods Sector as an aspiring data analyst and test your knowledge on basic Excel functions and shortcuts.
Learn MoreIntrо to Machine Learning
State-of-the-art machine learning algorithms have opened a whole new realm of possibilities for businesses to optimize their processes and create new product/service features, that maximize competitive advantages. Used in recommendation systems, fraud detection, spam filtering, self-driving cars, to name a few, these advanced algorithms are only getting more popular by the day. Take this free machine learning practice exam and test your knowledge on supervised, unsupervised and reinforcement machine learning, and their applications.
Learn MoreUseful Tools in Excel
What Excel lacks in data visualization tools compared to Tableau, or computational power for analyzing big data compared to Python, it compensates with accessibility and flexibility. Excel allows you to quickly organize, visualize and perform mathematical functions on a set of data, without the need for any programming or statistical skills. Therefore, it is in your best interest to learn how to use the various Excel tools at your disposal. This practice exam is a good opportunity to test your excel knowledge in the text to column functions, excel macros, row manipulation and basic math formulas.
Learn MoreFundamentals of Descriptive Statistics
Descriptive statistics helps us understand the actual characteristics of a dataset by generating summaries about data samples. The most popular types of descriptive statistics are measures of center: median, mode and mean. In this free practice exam you have been appointed as a Junior Data Analyst at a property developer company in the US, where you are asked to evaluate the renting prices in 9 key states. You will work with a free excel dataset file that contains the rental prices and houses over the last years.
Learn MoreExcel Functions
The majority of data comes in spreadsheet format, making Excel the #1 tool of choice for professional data analysts. The ability to work effectively and efficiently in Excel is highly desirable for any data practitioner who is looking to bring value to a company. As a matter of fact, being proficient in Excel has become the new standard, as 82% of middle-skill jobs require competent use of the productivity software. Take this free Excel Functions practice exam and test your knowledge on removing duplicate values, transferring data from one sheet to another, rand using the VLOOKUP and SUMIF function.
Learn MoreFundamentals of Inferential Statistics
While descriptive statistics helps us describe and summarize a dataset, inferential statistics allows us to make predictions based off data. In this free practice exam, you are a data analyst at a leading statistical research company. Much of your daily work relates to understanding data structures and processes, as well as applying analytical theory to real-world problems on large and dynamic datasets. You will be given an excel dataset and will be tested on normal distribution, standardizing a dataset, the Central Limit Theorem among other inferential statistics questions.
Learn MoreSQL SELECT Statement
SQL is one of the most popular and in-demand programming languages, because of its intuitive syntax, ubiquitous presence in the business world, and ability to query data and perform analysis. Therefore, possessing SQL skills will give you a significant career advantage in the modern data-driven workforce. Test your knowledge in the basics of SQL with this free SQL SELECT Statement practice exam designed by 365 Data Science instructor Martin Ganchev. These set of SQL questions will test your knowledge on creating databases, SQL Constraints, and the SQL Select Query by giving you a free .sql file containing company data, to work with.
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