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Complete PySpark & Google Colab Primer For Data Science (Udemy.com)

Develop Practical Machine Learning & Neural Network Models With PySpark and Google Colab

Created by: Minerva Singh

Last updated November 2024

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What you will learn

  • Get started with Google Colab- A powerful GPU powered cloud based environment for Python AI
  • Get Familiar With PySpark- Its Uses and Functioning
  • Work With PySpark Within the Google Colab Environment
  • Carry out Data Processing Using PySpark
  • Implement Common Statistical Analysis using PySpark
  • Implement Common Machine Learning Techniques- Classification and Regression on Real Data
  • Implement Deep Learning Models Within PySpark

How it compares

Against the other 205 rated Udemy courses in Artificial Intelligence on CourseDuck:

  • Rating4.5 out of 5higher than 58% of them
  • Reviews326#122 of 206 by number of reviews
  • Length4.4 hoursshorter than 52% of them
  • Last updatedNovember 2024earlier than 58% of them

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Course Description

YOUR COMPLETE GUIDE TO PYSPARK AND GOOGLE COLAB: POWERFUL FRAMEWORK FOR ARTIFICIAL INTELLIGENCE (AI)

This course covers the main aspects of the PySpasrk Big Data ecosystem within the Google CoLab framework. If you take this course, you can do away with taking other courses or buying books on PySpark based analytics as my course has the most updated information and syntax. Plus, you learn to channelise the power of PySpark within a powerful Python AI framework- Google Colab.

 In this age of big data, companies across the globe use Pyspark to sift through the avalanche of information at their disposal, courtesy Big Data. By becoming proficient in machine learning, neural networks and deep learning via a powerful framework, H2O in Python, you can give your company a competitive edge and boost your career to the next level!

LEARN FROM AN EXPERT DATA SCIENTIST:

My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment), graduate. I finished a PhD at Cambridge University, UK, where I specialized in data science models.

I have +5 years of experience in analyzing real-life data from different sources using data science-related techniques and producing publications for international peer-reviewed journals.

Over the course of my research, I realized almost all the data science courses and books out there do not account for the multidimensional nature of the topic.

This course will give you a robust grounding in the main aspects of working with PySpark- your gateway to Big Data

Unlike other instructors, I dig deep into the data science features of Pyspark and their implementation via Google Colab and give you a one-of-a-kind grounding

You will go all the way from carrying out data reading & cleaning to finally implementing powerful machine learning and neural networks algorithms and evaluating their performance using Pyspark.

Among other things:

  • You will be introduced to Google Colab, a powerful framework for implementing data science via your browser.

  • You will be introduced to important concepts of machine learning without jargon.

  • Learn to install PySpark within the Colab environment and use it for working with data

  • You will learn how to implement both supervised and unsupervised algorithms using the Pyspark framework

  • Implement both Artificial Neural Networks (ANN) and Deep Neural Networks (DNNs) with the Pyspark framework

  • Work with real data within the framework


NO PRIOR PYTHON OR STATISTICS/MACHINE LEARNING OR BIG DATA KNOWLEDGE IS REQUIRED:

You’ll start by absorbing the most valuable Pyspark Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in Python.

My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement Pyspark-based data science in real-life.

After taking this course, you’ll easily use the latest Pyspark techniques to implement novel data science techniques straight from your browser. You will get your hands dirty with real-life data and problems

You’ll even understand the underlying concepts to understand what algorithms and methods are best suited for your data.

We will also work with real data and you will have access to all the code and data used in the course. 

JOIN MY COURSE NOW!

I AM HERE TO SUPPORT YOU THROUGHOUT YOUR JOURNEY

INCASE YOU ARE NOT SATISFIED, THERE IS A 30-DAY NO QUIBBLE MONEY BACK GUARANTEE.

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Instructor Details

Minerva Singh

I completed a PhD (University of Cambridge, UK) in 2017 where I focussed on implementing data science techniques for quantifying the impact of forest loss on tropical ecosystems. I hold an MPhil (School of Geography and Environment) and an MSc (Department of Engineering) from Oxford University. I have more than 10 year's experience in conducting academic research (published in high level peer-reviewed international scientific journals such as PLOS One) and advising both non-governmental and industry stakeholders in data science, deep learning and earth observation (EO) related topics.

I have a strong track record in implementing machine learning, data visualization, spatial data analysis, deep learning and natural language processing tasks using both R and Python. In addition to being educated at the best universities in the world, I have honed my statistical and data analysis skills through many MOOCs, including The Analytics Edge (R based statistics and machine learning course offered by EdX), Statistical Learning (R-based Machine Learning course offered by Stanford online) and the IBM Data Science Professional certificate Track. I specialise in a variety of topics ranging from deep learning (Tensorflow, Keras) to machine learning to spatial data analysis (including EO data processing), data visualizations, natural language processing, financial analysis among others. I have acted as a peer reviewer on highly

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Reviews

4.5

326 ratings on Udemy

Select a bar to show only those reviews.Select the bar again to show every rating.

By Wisdom Gbagan on 5/22/2025

This instructor does a great job, especially in the machine learning section where the model building is explained step-by-step in a really clear way.

By Zakir Haldar on 10/20/2024

Fantastic experience using this guided course. It is effective in outlining and establishing the fundamentals of Apache Spark. Jose did a great job explaining; keep it up.

By Rey Fowler on 3/1/2024

The constant counter-clockwise circling of the instructor's cursor was insanely distracting to the point where I could not look directly at the screen while the video was playing - I would have to stop, read the contents of the slide or page, and then resume. Additionally, it was really strange that the instructor had to copy and paste a "{" and "}" - like why couldn't she just hit shift+] to get } like the rest of us? Is her keyboard broken? There was also several cuts where she'd just stop mid one idea and never get back to it, like when she forgot to run the cell with a variable and then got an error saying that variable had not been assigned and then it cut and she moved on to something else.

By Rossey on 11/26/2023

The course has vast potential for practical applications. New dimensions of the concept have been brilliantly explained by the instructor in her lectures.

By Ravi Srivastava on 10/1/2021

The course is beyond my expectations. I hope to make use of the concept to significantly enhance the quality of my work. The instructor is well-versed with the subject and has explained the concept with utmost clarity.

By Raj Kumar Majumdar on 8/31/2021

The information contained in the course is useful and valuable. It has immense potential for practical applications. The course is ideally suited for my work. The instructor is well-versed with the minutest details of the concept and her delivery is engaging.

By Rishilal Yadav on 8/2/2021

the course contains valuable and useful information. The instructor has structured the lecture in easy-to-understand manner. Her knowledge of the subject and delivery is impressive.

By Rajesh Kumar on 7/24/2021

The course contains useful and valuable information on data science. The concepts in the course are immensely suitable for my work and i see great benefit from opting for this course. The instructor is very clear in her explanation of the concepts.

By RKM singh on 7/8/2021

Taking this course is great learning experience for me. The lectures in the course have significantly cleared many doubts in my mind about the concepts. The delivery of the instructor is very vivid and straightforward.

By Yang Li on 5/30/2021

very disappointed. I don't think the learning goal is clearly established and the course is not well structured as well, especially for the setup. The instructor always made coding errors in the video. Don't buy the course

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Overall Score : 90 / 100