Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist's toolkit. This course covers regression analysis, least squares and inference using regression models. Special cases of the regression model, ANOVA and ANCOVA will be covered as well. Analysis of residuals and variability will be investigated.

Functional programming is a style of programming that is characterized by short functions, lack of statements, and little reliance on variables. You will learn what functional programming is, and how you can apply functional programming in Python. In this video course, we will learn what functional programming is, and how it differs from other programming styles, such as procedural and object-oriented programming. We will also learn why and when functional programming is useful, and why and when it makes programs unnecessarily complex. Then we go on to explore lambda expressions, which are short one-line functions, and are the purest form of functional programming that Python offers.

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation.

Have you decided to learn Python as your first programming language? Or just heard that Python is one of the best modern languages to learn? Python is an incredibly powerful language and that can be used in almost any situation. That's why I chose Python as the first course in the "If You Can Cook, You Can Code" Series. Are you a beginner to programming?

Prerequisites: No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided. Taught by a Stanford-educated, ex-Googler and an IIT, IIM - educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce. The course is shy but confident: It is authoritative, drawn from decades of practical experience -but shies away from needlessly complicating stuff.

Python is an object-orientated language that closely resembles the English language which makes it a great language to learn for beginners as well as seasoned professionals. Examples sites that use Python are Instagram, YouTube, Reddit, NASA, IBM, Nokia, etc. Python is one of the most widely used programming languages in the AI field of Artificial Intelligence thanks to its simplicity. It can seamlessly be used with the data structures and other frequently used AI algorithms. This is because it is the ideal language to work with for general purpose tasks. Experienced coders tend to stay more organized and productive when working with Python, as well.

In this article, I want to talk about artificial intelligence (AI) and how it is transforming the training and education sector. Before we get to that part, let's quickly take a look at how formal and informal education has evolved side by side throughout history. Formalized education has existed for thousands of years. Greek philosophers used to deliver lectures and teach their students long before the time of the Romans. It goes back hundreds of years before the Julian calendar was even introduced.

Python is a big deal. More and more beginner programmers are choosing it as their first language to learn, which means its future is more than just bright - it's dazzling. It makes coding faster, easier and fun. When combined with the object oriented programming approach these qualities are further enhanced, which means Python is virtually unstoppable. If you want to future-proof your programming skills, this is exactly what you need to learn.

About this course: This introductory course is developed for high level business people (and those on their way) who want a broad understanding of new Information Technologies and understand their potential for business functions (e.g. This is not a course for people looking for guidance on how to become a deep technical expert or implement these technologies. From Blockchain over Artificial Intelligence to Virtual Reality technologies: This course will empower business leaders to embrace the concepts and bring the state of the art information technologies into their organizations to improve client and customer engagement and ultimately the bottom line of their businesses. Instead of digital disruption, the new technologies and management methods will become the foundation of a Digital Transformation journey for better customer relationship management and client satisfaction. The content is structured in a way that promotes discussions on challenges that business management and marketing functions face due to the rise of new technologies such blockchain, cryptocurrencies, internet of things (IoT), virtual, mixed and augmented reality (VR/AR), artificial intelligence (AI) and big data.

A large portion of the field of statistics is concerned with methods that assume a Gaussian distribution: the familiar bell curve. If your data has a Gaussian distribution, the parametric methods are powerful and well understood. This gives some incentive to use them if possible. Even if your data does not have a Gaussian distribution. It is possible that your data does not look Gaussian or fails a normality test, but can be transformed to make it fit a Gaussian distribution.