Learn Advance Your Future.

Gain a high-level understanding of Data Science in the newly introduced course-Data Science for Managers. Guide data-driven projects with more confidence.

This Statistics preparation material will cover the important concepts of Statistics syllabus. It contains chapters discussing all the basic concepts of Statistics with suitable examples.

This page is a complete repository of statistics tutorials which are useful for learning basic, intermediate, advanced Statistics and machine learning algorithms with SAS, R and Python.

Python for beginners in Data Science, Machine Learning and Deep Learning

Wanted to learn Machine Learning from a live instructor online ? Register for this 45 hour instructor led, online course on Machine Learning in Python. Everything on this page is taught at 1 hour a day on weekdays. This course is designed for absolute beginner's in mind.

Analytics Academy helps you learn about Google's measurement tools so that you can grow your business through intelligent data collection and analysis.

We analyze your website to identify SEO errors, keyword opportunities, and competition.

Matplotlib is a popular Python library that can be used to create data visualizations quite easily. It is probably the single most used Python package for 2D-graphics along with limited support for 3D-graphics.

This blog article is an excerpt from the Python Basics Handbook created for the simple purpose of making the reader understand the beauty and simplicity of the Python language.

Understand the Concepts, Techniques and Mathematical Frameworks Used by Experts in Machine Learning

Here I'd like to walk through my study notes with the most explicit step-by-step directions to introduce you to the world of R.

Learning from data in order to gain useful predictions and insights. This course introduces methods for five key facets of an investigation: data wrangling, cleaning, and sampling to get a suitable data set; data management to be able to access big data quickly and reliably; exploratory data analysis to generate hypotheses and intuition; prediction based on statistical methods such as regression and classification; and communication of results through visualization, stories, and interpretable summaries.

The following manuals for R were created on Debian Linux and may differ from the manuals for Mac or Windows on platform-specific pages, but most parts will be identical for all platforms.

Welcome to the World of Python. Are you eager to know and learn Python _ The Most Powerful and Popular Programming Langauge? Then start with this Python Tutorial now.

If you go through these 7 articles, you will learn how to do basic data cleaning, data formatting and analytics via the command line. On the top of that you will have your own data server to practice _ we will use that not only here, but in my future SQL and Python tutorials too.

In my Python for Data Science articles I'll show you everything you have to know. I'll start from the very basics _ so if you have never touched code, don't worry, you are at the right place. I'll focus only on the data science related part of Python _ and I will skip all the unnecessary and impractical trifles.

This handcrafted guide exists to provide both novice and expert Python developers a best practice handbook for the installation, configuration, and usage of Python on a daily basis.

This tutorial introduces the reader informally to the basic concepts and features of the Python language and system. It helps to have a Python interpreter handy for hands-on experience, but all examples are self-contained, so the tutorial can be read off-line as well.

You'll need to know a bit of Python. For a refresher, see the Python tutorial. To work the examples, you'll need matplotlib installed in addition to NumPy.