Data Science Course Notes
Enhance your learning journey with in-depth data science lecture notes. Deepen your understanding of core concepts in data science, statistics, probability, Python, and machine learning.Course notes are the perfect complementary online data science study materials. They help you grasp fundamental concepts, refresh your memory when preparing for exams, and get a taste of our learning style.
Committed to your career success and development, we at 365 Data Science support you throughout your learning journey with free resources designed to enhance and guide your education. Our rich selection covers everything from data science notes for beginners to simplified explanations of advanced topics. Choose a subject you wish to master, download our free PDF course notes, and start learning.
Machine Learning with K-Nearest Neighbors
K Nearest Neighbors - also known as KNN, is one of the most popular AI algorithms thanks to its simplicity of use and relatively high level of accuracy compared to more sophisticated algorithms. The KNN machine learning model has a very fast training process, making it a good machine learning algorithm to analyze multiclass datasets right off the bat. In these free Machine Learning with KNN pdf course notes, you will learn about the algorithm’s pros and cons, defining distance metrics, the important steps in creating a KNN model and the most commonly used performance metrics.
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Data Literacy Intro
Data has become a universal language for modern businesses and organizations who strive to use it strategically to gain better insights about the market. If you aspire to become proficient in the language of data and be at the forefront of business growth, the first step is to familiarize yourself with the concepts in the free pdf course notes on introduction to data literacy. Learn what defines a data literate individual, the purpose of data literacy in the modern data ecosystem, what data-driven decision making looks like and what are the benefits of working with data.
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Data Literacy
Data literacy is the ability to work with, comprehend and communicate data that generates logarithmic amount of value across all business departments. In the global workplace, where data usage and automation are rapidly positioning themselves at the heart of business operations, the need for a data literate workforce has never been higher. Studying these free pdf course notes on data literacy by top-data executive Oliver Maugain will help you leverage your newly learned data skills in this highly rewarding job market, which is experiencing a systemic data talent shortage.
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Interpreting Data
By now you should have a solid understanding of data terminology, data quality assessment, different data storage systems, AI applications and Machine Learning techniques. We are going to conclude the series of free pdf data literacy course notes with data interpretation- a key component in the evaluation of financial assets on the financial market, prediction of market behavior, problem-solving in the fields of medicine and etc.
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Reading Data
The consequences of businesses who do not perform data quality assessments can be devastating to business growth. Poor data quality can lead to executing the wrong business strategies, reduced efficiency, increased financial costs, damaged customer relationships and ultimately to bankruptcy. Therefore, in the third part of the free pdf course notes on data literacy, we provide information on how to read data, by distinguishing between good and bad data, what are the negative impacts of poor data quality, and the various descriptive methods that characterize a dataset.
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Using Data
AI is the modern day facilitator of human productivity that allows for human intelligence to execute feats that would have been considered impossible a few decades ago. As modern businesses integrate AI and its Machine Learning capabilities with their decision-making and operational activities, the need for data competent individuals who can help with the integration process has never been higher. Therefore, in the Using Data free pdf course notes we will familiarize you with the practical applications of AI and ML, the types of supervised and unsupervised machine learning techniques and natural language processing abilities of AI.
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Understanding Data Literacy
Thanks to the mass digitalization of the world, information has become the oil of the 21st century that sustains the engines of modern businesses. As of 2021, there are approximately 4,66 billion internet users! Imagine the amount of data, that consumers leave behind that just waits to be stored and processed by businesses. Therefore, in these free pdf course notes on Understanding Data Literacy, we are going to identify various types of data, the three defining properties of Big Data and the different methods for storing data.
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Machine Learning with Naïve Bayes
Naïve Bayes Classifier is a supervised classification machine learning algorithm inspired by the Bayes Theorem. Its ability to make intuitive real time-predictions from small non-linear sets makes it perfect for consumer behavior predictions, recommendation systems and text analysis - news article categorization, email category filtering and sentiment analyses. In the free Machine Learning with Naïve Bayes pdf course notes we are going to build upon your sklearn Naïve Bayes skills by going over the algorithm’s computational capabilities, outlining the 7 steps in creating a supervised machine learning model and identifying 6 relevant metrics to use for performance evaluation.
Learn MoreCheck out our most helpful downloadable data science course notes according to our students and expert team of instructors—available for free in PDF format.
Statistics
Before we can build machine learning algorithms or extract valuable insight from our data we need to transform the raw data into an understandable format and check its quality. In other words, we need to do data preprocessing, which requires statistical knowledge every step along the way. Therefore, learning statistics is a must-have skill when doing data science. In these free pdf course notes, we will be covering the fundamentals of statistics, the different types of distributions, confidence intervals and respective formulas, calculation of covariance and correlation, hypotheses testing, and much more
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Intro to Python
Python is the top programming language in both the TIOBE and PYPL Index, making it one of the most popular programming languages worldwide. This is all thanks to its intuitive, beginner-friendly syntax and wide range of real-world applications like web development, scientific computing, game development, AI & machine learning, graphic design etc. But before you can dwell in this vast world of possibilities, you need to learn the basics of Python. We introduce you the free pdf Intro to Python course notes where you will learn basic Python syntax, how to create and use functions, conditional statements , iteration and much more.
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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 Strategy
Companies that sit on treasure troves of data but have no defined or bad data strategy not only fail to collect dividends from their wealth of data, but also incur great financial and reputational losses. In these free pdf course notes on Data Strategy, you will learn what is the purpose of a company’s data strategy, how data strategy helps build competitive advantage, how to create technology and data infrastructures that support business growth and much more.
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Check out our most helpful downloadable data science course notes according to our students and expert team of instructors—available for free in PDF format.
Statistics
Before we can build machine learning algorithms or extract valuable insight from our data we need to transform the raw data into an understandable format and check its quality. In other words, we need to do data preprocessing, which requires statistical knowledge every step along the way. Therefore, learning statistics is a must-have skill when doing data science. In these free pdf course notes, we will be covering the fundamentals of statistics, the different types of distributions, confidence intervals and respective formulas, calculation of covariance and correlation, hypotheses testing, and much more
Learn MoreIntro to Python
Python is the top programming language in both the TIOBE and PYPL Index, making it one of the most popular programming languages worldwide. This is all thanks to its intuitive, beginner-friendly syntax and wide range of real-world applications like web development, scientific computing, game development, AI & machine learning, graphic design etc. But before you can dwell in this vast world of possibilities, you need to learn the basics of Python. We introduce you the free pdf Intro to Python course notes where you will learn basic Python syntax, how to create and use functions, conditional statements , iteration and much more.
Learn MoreProbability
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.
Learn MoreData Strategy
Companies that sit on treasure troves of data but have no defined or bad data strategy not only fail to collect dividends from their wealth of data, but also incur great financial and reputational losses. In these free pdf course notes on Data Strategy, you will learn what is the purpose of a company’s data strategy, how data strategy helps build competitive advantage, how to create technology and data infrastructures that support business growth and much more.
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