Python: Your First Step Toward Data Science [Video]

More Information
  • Set up your Python data science environment
  • Master core Python concepts and import your datasets into Python
  • Functions, lambdas, and string functions for data cleaning
  • Classes, objects, and tuples for building regression models with scikit-learn
  • List slicing and class parameters to build classification models
  • Generators for grouping relevant items using clustering

Python is one of the top languages today and is very popular with Data Scientists and Data Analysts. Whether you're a novice or an expert, this course will help you take the next step to becoming a Data Scientist..

 This fast-paced, action-packed course will maximize your time; it's designed from the ground up to familiarize you with the basics of Python, so you can pursue your data science dreams. With this course, you will be up-and-running with Python Data Science in no time, helping you prove your value and expertise today and build your CV and skill set for tomorrow.

This course will get you up-to-speed with using Python, without resorting to a collection of disconnected, unrelated pieces of information. Thus, you can take the next step toward advancing your career in data science.

The code bundle for this course is available at -

Style and Approach

The course is full of hands-on instructions, interesting and illustrative visualizations, and clear explanations from an entrepreneur building his product in pure Python. It is packed full of useful tips and relevant advice learned from shipping real, commercial products. Throughout the course, we maintain a focus on practicality and getting things done, not fancy programming concepts and theory.

  • Start your Python data science journey.
  • Practical, get-it-done style focuses on results and brings you up-to-speed with Python, so that you can start a new data science project, or enter an existing data science project, with ease.
  • Comprehensively packs everything about data science and Python into 3 hours.
Course Length 2 hours 25 minutes
ISBN 9781788994415
Date Of Publication 25 Apr 2019


Rudy Lai

Colibri Digital is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help its clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas such as big data, data science, machine learning, and Cloud computing.

Over the past few years, they have worked with some of the World's largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the World's most popular soft drinks companies, helping each of them to better make sense of its data, and process it in more intelligent ways.
The company lives by its motto: Data -> Intelligence -> Action.

Rudy Lai is the founder of QuantCopy, a sales acceleration startup using AI to write sales emails for prospects. By taking in leads from your pipelines, QuantCopy researches them online and generates sales emails from that data. It also has a suite of email automation tools to schedule, send, and track email performance—key analytics that all feed back into how our AI generates content.

Prior to founding QuantCopy, Rudy ran HighDimension.IO, a machine learning consultancy, where he experienced first-hand the frustrations of outbound sales and prospecting. As a founding partner, he helped startups and enterprises with HighDimension.IO's Machine-Learning-as-a-Service, allowing them to scale up data expertise in the blink of an eye.

In the first part of his career, Rudy spent 5+ years in quantitative trading at leading investment banks such as Morgan Stanley. This valuable experience allowed him to witness the power of data, but also the pitfalls of automation using data science and machine learning. Quantitative trading was also a great platform from which you can learn about reinforcement learning and supervised learning topics in depth and in a commercial setting.

Rudy holds a Computer Science degree from Imperial College London, where he was part of the Dean's List, and received awards such as the Deutsche Bank Artificial Intelligence prize.