Complete PySpark & Google Colab Primer For Data Science

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

4.40 (143 reviews)
Udemy
platform
English
language
Data & Analytics
category
instructor
1,191
students
4.5 hours
content
Nov 2022
last update
$59.99
regular price

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

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.

Content

Welcome To The Course

What Is This Course About?
Data and Code
Python Installation
Start With Google Colaboratory Environment
Google Colabs and GPU
Google Colab Packages
What is PySpark?
Run PySpark Within Google CoLab

Get Your Data Into Google Drive

Mount Your Drive
Opening a Jupyter Notebook
Accessing Data Within the Drive
Upload Data From a Local Drive
Install New Packages

Getting Started With Spark Within Google Colab

Let's Start Sparkling
Troubleshoot
In Case Everything Is Properly Installed.
Read CSV into the Spark Framework
Basic Data Exploration
Data Summarisation
Data Standardisation
User Defined Functions (UDF)

Basic Statistical Modelling

Correlation Theory
Implement a Correlation Analysis
OLS
Implement an OLS Model
ElasticNet Regression
What are GLMs?
Implement a Logistic Regression Model
Theory of Accuracy Assessment
The Anatomy of a PySpark Model
Dealing With a Mixed Dataset

Welcome to Machine Learning

What Is Machine Learning?
ML description
RF Theory
Implement a Multi-Class Random Forest Model
Evaluate the RF Model Accuracy
Random Forest Regression
Introduction to Pipelines
Using Pipelines
Unsupervised Classification-k means theory
Implement a K-Means Model

Introduction To Artificial Intelligence (AI)

What Is AI?
Theory Behind ANN and DNN
Set Up a Neural Network Problem
Model Fitting
ANN With a Mixed Dataset
Activation Function

Screenshots

Complete PySpark & Google Colab Primer For Data Science - Screenshot_01Complete PySpark & Google Colab Primer For Data Science - Screenshot_02Complete PySpark & Google Colab Primer For Data Science - Screenshot_03Complete PySpark & Google Colab Primer For Data Science - Screenshot_04

Reviews

Miklos
October 6, 2023
The instructor may be very good in this area, but what works in a lecture hall can easily fail when online education is the goal. The examples are too specific and only confuse the point, leaving many errors uncorrected. The presentation is amateur. The typing skills are pathetic and the constant mouse dragging is terribly irritating. It completely lacks post-production, which is both annoying and ridiculous. It's nice to find this production online for free, but it's far from Udemy's professionalism.
Anonymized
August 18, 2023
The course contains vital and valuable information on the subject. The instructor has brilliantly explained finer points of the course.
Anonymized
August 8, 2023
The instructor has thorough knowledge of the subject. Her lectures are interesting and her style of teaching is engaging.
Anonymized
March 31, 2023
los videos se pueden ver pero no los documentos, porque en vez de tener el documento tiene un link a un drive, que no está ligado
Thomas
January 11, 2023
Lots of errors in her code that she did not bother to remedy. Plenty of cases where she would run into an error, and just end the lecture leaving the student guessing as to how to fix it. Also plenty of cases where she would show code that she was not running, yet when the code was run, errors came up. Overall really good information, but at times the instruction was lacking.
Lisbet
December 30, 2022
Very good Pyspark course but setting up is clunky. Once I got PySpark going in Colab, then I really learnt a lot
Neeraj
July 9, 2022
This course will certainly enhance the quality of my work as well as my knowledge base significantly.
Sweta
July 5, 2022
It is a well-structured course which is immensely beneficial to me. My knowledge base will enhance several notches.
Marks
June 13, 2022
The course is more than my expectations. It contains high-value information and has immense potential for me.
Mario
April 22, 2022
The course is beyond my expectations. It will certainly enhance the quality of my work as well as my knowledge base significantly.
Ramakrishna
February 14, 2022
The course is above expectations. It contains high-value information and has immense potential for practical applications.
Ravi
October 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.
Raj
September 1, 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.
Rishilal
August 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.
Rajesh
July 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.

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3365382
udemy ID
7/25/2020
course created date
4/1/2021
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