Web Development
Data Science
Python
SQL
JavaScript
Artificial Intelligence
IT & Software
IT Certifications
Hacking
AWS
Arduino
DevOps
3D Modeling
Graphic Design
Photoshop
Drawing
Digital Painting
UX Design
Business
Data Analysis
Communication Skills
Project Management
Leadership & Management
Human Resources
Digital Marketing
Social Media Marketing
Marketing
SEO
Google Analytics
Branding
Excel
Office Productivity
SAP
PowerPoint
Microsoft Access
SharePoint
Finance & Accounting
Trading & Investing
Accounting
Bitcoin
Personal Finance
Video Editing & Animation
Photography
Adobe Premier Pro
Adobe Lightroom
Personal Development
Productivity
Career Development
Life Coaching
Health & Fitness
Meditation & Mindfulness
Yoga
Music
Music Production
Guitar
Piano
Singing
Language Learning
Teaching & Academics
Engineering
Math
LifestyleFrom 0 to 1 : Spark for Data Science with Python (Udemy.com)
Get your data to fly using Spark for analytics, machine learning and data science
Created by: Loony Corn
Last updated February 2018
What you will learn
- Use Spark for a variety of analytics and Machine Learning tasks
- Implement complex algorithms like PageRank or Music Recommendations
- Work with a variety of datasets from Airline delays to Twitter, Web graphs, Social networks and Product Ratings
- Use all the different features and libraries of Spark : RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming and GraphX
How it compares
Against the other 461 rated Udemy courses in Data Science on CourseDuck:
- Rating4.2 out of 5higher than 9% of them
- Reviews779#176 of 462 by number of reviews
- Length8.3 hoursshorter than 50% of them
- Last updatedFebruary 2018earlier than 97% of them
Course Description
Get your data to fly using Sparkfor analytics, machine learning and data science
Lets parse that.
What's Spark?
If you are an analyst or a data scientist, you'reused to having multiple systems for working with data. SQL, Python, R, Java, etc. With Spark, you have a single engine where you can explore and play with large amounts of data, run machine learning algorithms and then use the same system to productionize your code.
Analytics:
Using Spark and Python you can analyze and explore your data in an interactive environment with fast feedback. The course will show how to leverage the power of RDDs and Dataframes to manipulate data with ease.
Machine Learning and Data Science:
Spark's core functionality and built-in libraries make it easy to implement complex algorithms like Recommendations with very few lines of code. We'll cover a variety of datasets and algorithms includingPageRank, MapReduceand Graph datasets.
What's Covered:
Lot's of cool stuff ..
Music Recommendations using Alternating Least Squares and the Audioscrobbler datasetDataframes and Spark SQL to work with Twitter dataUsingthe PageRank algorithm with Google web graph datasetUsing Spark Streaming for stream processingWorking with graph data using theMarvel Social network dataset
.. and of course all the Spark basic and advanced features:
Resilient Distributed Datasets, Transformations (map, filter, flatMap), Actions (reduce, aggregate)Pair RDDs , reduceByKey, combineByKeyBroadcast and Accumulator variablesSpark for MapReduceThe Java API for SparkSpark SQL, Spark Streaming, MLlib and GraphFrames (GraphX for Python)Who this course is for:
Yep! Analysts who want to leverage Spark for analyzing interesting datasetsYep! Data Scientists who want a single engine for analyzing and modelling data as well as productionizing it. Yep! Engineers who want to use a distributed computing engine for batch or stream processing or both
Udemy Discount
The discount is applied through our link. Open the course from here and Udemy's current promotional price is applied at checkout on most courses, no code to type.
Some courses are excluded from Udemy's promotions. If the price does not drop, clear your browser cookies and use the button again.
Instructor Details
- 4.2 Rating
779 Reviews
Loony Corn
Loonycorn is us, Janani Ravi andVitthal Srinivasan. Between us, we have studied at Stanford, been admitted to IIM Ahmedabadand have spent years working in tech, in the Bay Area, New York, Singapore and Bangalore.
Janani: 7 years at Google (New York, Singapore); Studied at Stanford; also worked at Flipkart and Microsoft
Vitthal: Also Google (Singapore) and studied at Stanford; Flipkart, Credit Suisse and INSEAD too
We think we might have hit upon a neat way of teaching complicated tech courses in a funny, practical, engaging way, which is why we are so excited to be here on Udemy!
We hope you will try our offerings, and think you'll like them :-)
More courses by Loony Corn
GCP: Complete Google Data Engineer and Cloud Architect Guide (2018)
4.0 (7,369 Reviews)
Provider: Udemy
Time: 27.9h
$94.99
From 0 to 1: The Cassandra Distributed Database (2016)
4.1 (2,613 Reviews)
- Provider: Udemy
- Time: 5.9h
$59.99
From 0 to 1: Data Structures & Algorithms in Java (2019)
4.5 (1,381 Reviews)
- Provider: Udemy
- Time: 15h
$14.99
Learn By Example: Hadoop, MapReduce for Big Data problems (2018)
4.5 (1,209 Reviews)
- Provider: Udemy
- Time: 13.7h
$79.99
Learn by Example : HBase - The Hadoop Database (2018)
4.4 (1,156 Reviews)
- Provider: Udemy
- Time: 4.9h
$54.99
Kubernetes On The Cloud & The CNCF CKA Certification (2018)
4.1 (1,108 Reviews)
- Provider: Udemy
- Time: 8.3h
$13.99
More Data Science courses
Master statistics & machine learning: intuition, math, code (2026)
4.9 (3,077 Reviews)
- Provider: Udemy
- Time: 38.3h
$124.99
Reviews
By Shobana Santhanagopalan on 9/12/2020
Please change the volume of the music in the end. It is so loud that everything that was learnt in the video just gets replaced by the music
By Rahul Bavirisetty on 9/1/2020
Its quite helpful
By Saheb chourasia on 8/10/2020
The Instructor is great at teaching.
She knows what to tell and when to tell.
By David Henderson on 7/26/2020
It is simply outdated and abandoned in 2018, teaching RDDs rather than dataframes using Python 2.7 rather than a variant of 3.
I have no doubt that at the time of release it was a good course and my rating reflects its relevance to the topic of pyspark today in 2020, not the work of the authors.
By Amit Gupta on 7/25/2020
One of the best courses I have come across on Spark and in general around bigdata and Hadoop. Starts with giving the theory and basics before building upon the practical usage.
By Danny Sinang on 5/27/2020
I like the story-telling approach. Explaining the why before jumping into the what's and how's works for me.
By Sagnik Dasgupta on 5/15/2020
very detailed explanation with diagrams. The only thing need to improve is quiz or practice tests to validate the knowledge gained
By Arti Rajvaidhya on 5/1/2020
nice
By Vinit Galgali on 4/4/2020
explaination with pictures , images will be much much better nd not only words
By Subramonia Pillai on 3/16/2020
keep up the good work.
By Mayasushma on 2/2/2020
The course gives the basic understanding of spark. it could have been better if at some sessions of the course the context is explicitly explained.
By Sreekanth Payyavula on 1/18/2020
The articulation needed to understand a complex topic is good. The tutor goes great lengths to explain the concepts and the examples have been taken which are interesting and relevant.
Quality Score
No CourseDuck member has rated this course yet. Taken it? Give each part a thumbs up or down.
Overall Score : 84 / 100
- Video Duration:
8.3h - Price: $69.99
- Provider: Udemy
- Updated:
February 2018 - Level:
All Levels - Language:
English - Certificate:
Yes
30-day money-back guarantee on most paid courses
Udemy Coupon Price Tracker
