PySpark Foundation for Data Analysis | Beginners

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Akash Sunil Pawar

56:46

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1. Introduction to Course.mp4

00:45

2. What is Data Analysis.mp4

00:43

3. Data analysis in Elections.mp4

00:40

4. Data Analysis in Cricket.mp4

01:37

5. Learning Outcomes.mp4

01:05

6. Insights we will get from data.mp4

02:20

7. Upload the data.mp4

01:01

8. Read the data.mp4

00:40

9. Understanding the data.mp4

06:17

10. Cleaning the data.mp4

01:36

11. Understanding data part 2.mp4

01:38

12. Total runs in an inning by a team.mp4

04:05

13. Highest runs scored by a Team.mp4

02:54

14. Lowest score by a team.mp4

00:50

15. Validation of results.mp4

00:50

16. Highest Run Scorers for RCB.mp4

02:27

17. Highest Run scorers batting first.mp4

01:29

18. Highest run scorers batting second.mp4

03:14

19. Creating buckets of overs.mp4

02:42

20. Bucketwise runs scored.mp4

01:19

21. Run rate in each phase.mp4

03:13

22. Best batters in powerplay.mp4

01:57

23. Best batters in Death.mp4

01:18

24. Understanding Bowlers data.mp4

03:12

25. Most wickets against RCB by a bowler.mp4

02:44

26. Most wickets in powerplay.mp4

01:50

27. Best bowler in Death.mp4

01:27

28. Recap and Summary.mp4

02:53

Description

Data Engineering, PySpark, Data Analysis, Coding exercise, Data Analytics

What You'll Learn?

Fundamentals of PySpark
Hands on experience in PySpark
Understanding of data using PySpark
Performing various data analysis operations
Data Analytics
Analysis of data

Who is this for?

Anyone with an interest in Data engineering and data analysis

What You Need to Know?

There are no pre-requisites for the course. We will learn and practice together.

Basic Python knowledge is a plus

Good to have watched 1st part of this course

More details

Description
Have you ever wondered How Big Data is helping Teams Win Big at the T20 World Cups/IPL?
In this course we will focus on very basic Data analysis to get useful insights on IPL dataset with the help of PySpark.

Learn to code PySpark like a real world developer. Here our major focus will be on Practical applications of PySpark and bridge the gap between academic knowledge and practical skill.

About PySpark:
Learn the latest Big Data Technology - Spark! And learn to use it with one of the most popular programming languages, Python!
One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Spark! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Spark to solve their big data problems!
Spark can perform up to 100x faster than Hadoop MapReduce, which has caused an explosion in demand for this skill! Because the Spark 2.0 DataFrame framework is so new, you now have the ability to quickly become one of the most knowledgeable people in the job market!

What you will learn :
What is Data Analysis
Data analysis in Elections
Data Analysis in Cricket
Big Data Cleaning
Calculating Averages
Manipulating Data
GROUPBY
Aggregations
Sorting
Joins in PySpark
Prerequisites :
Some basic programming skills (Not Mandatory)
Will to implement theoretical knowledge in pratical.

Who this course is for:
Beginners who want to learn Big Data or experienced people who want to transition to a Big Data role
Big data beginners who want to learn how to code in the real world
Aspiring candidates for data analytics or data engineering role
Who this course is for:
Anyone with an interest in Data engineering and data analysis

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Akash Pawar is a Certified Google cloud Associate engineer. He has completed Bachelor of Technology in Electronics Engineering from National Institute of Technology (NIT, Rourkela) and has years of experience as a professional data engineer and trainer for ETL operations using PySpark. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data engineering to help other people learn the power of programming, the ability to analyze data, and the skills needed to present the data in clear and beautiful visualizations. Currently he works as the Data Engineer in Fractal Analytics.

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