Big Data & Analytics using R (MCA338) crash course, Online MCA, Semester 3:
This subject introduces big data and the Hadoop ecosystem, covering HDFS, MapReduce, Pig, Hive, HBase and Big SQL, followed by data analysis and machine…
- 17 video lessons
- 5h 58m
- Study notes
- 85 quiz questions
- Assignment
17 lessons in Big Data & Analytics using R
Each lesson pairs one topic with a hand-picked video, trimmed to the part that teaches it.
About this subject
This subject introduces big data and the Hadoop ecosystem, covering HDFS, MapReduce, Pig, Hive, HBase and Big SQL, followed by data analysis and machine learning in R. After it you will be able to store and process large datasets on Hadoop, query them with Pig and Hive, and load, explore and model data in R.
- 1
Introduction to Big Data and Big Data Analytics
Module I, Introduction To BIG Data and Hadoop: Types of Digital Data, Introduction to Big Data, Big Data Analytics
Introduction to Big Data Analytics 🔥· Perfect Computer Engineer· 8 min
Study notes 5 quiz questionsWatch lesson - 2
Hadoop Basics: History, Unix Tools vs Hadoop, Streaming
Module I, Introduction To BIG Data and Hadoop: History of Hadoop, Apache Hadoop, Analysing Data with Unix tools, Analysing Data with Hadoop, Hadoop Streaming
Lec-133: Introduction to Hadoop🐘| What is Hadoop🐘| Hadoop Framework🖥· Gate Smashers· 9 min
Study notes 5 quiz questionsWatch lesson - 3
Hadoop Ecosystem and IBM InfoSphere BigInsights
Module I, Introduction To BIG Data and Hadoop: Hadoop Echo System, IBM Big Data Strategy, Introduction to Infosphere BigInsights and Big Sheets
Hadoop🐘Ecosystem | All Components Hdfs🐘,Mapreduce,Hive🐝,Flume,Sqoop,Yarn,Hbase,Zookeeper🪧,Pig🐷· Gate Smashers· 11 min
Study notes 5 quiz questionsWatch lesson - 4
HDFS Design, Concepts and Command Line
Module II, HDFS(Hadoop Distributed File System): The Design of HDFS, HDFS Concepts, Command Line Interface, Hadoop file system interfaces, Data flow
BIG DATA ANALYTICS - Design of Hadoop Distributed Files System (HDFS) | HDFS Concepts· Madana Mohana R's ICT Channel· 37 min
Study notes 5 quiz questionsWatch lesson - 5
Data Ingestion with Flume, Sqoop and Hadoop Archives
Module II, HDFS(Hadoop Distributed File System): Data Ingest with Flume and Scoop and Hadoop archives
Big Data & Hadoop Full Course - Learn Hadoop In 10 Hours | Hadoop Tutorial For Beginners | Edureka· edureka!· 28 min
Study notes 5 quiz questionsWatch lesson - 6
Hadoop I/O: Compression, Serialization and Avro
Module II, HDFS(Hadoop Distributed File System): Hadoop I/O: Compression, Serialization, Avro and File-Based Data structures
Data Serialization in Big Data Analyticts· Sirisha Lectures· 18 min
Study notes 5 quiz questionsWatch lesson - 7
Anatomy of a MapReduce Job Run and Failures
Module III, Map Reduce: Anatomy of a Map Reduce Job Run, Failures, Job Scheduling
Anatomy of MapReduce, Failures in MapReduce & YARN | BDA - 2.7· Ayan Memon· 14 min
Study notes 5 quiz questionsWatch lesson - 8
MapReduce Shuffle, Sort and Task Execution
Module III, Map Reduce: Shuffle and Sort, Task Execution
Master MapReduce in One Video | Anatomy, Failures, Shuffle & Sort, Task Execution Explained· UniqueAcademy 2.0· 27 min
Study notes 5 quiz questionsWatch lesson - 9
MapReduce Types, Formats and Features
Module III, Map Reduce: Map Reduce Types and Formats, Map Reduce Features
MapReduce Types and Formats | BDA - 2.6· Ayan Memon· 5 min
Study notes 5 quiz questionsWatch lesson - 10
Apache Pig and Pig Latin Tutorial
Module IV, Hadoop Eco System: Pig : Introduction to PIG, Execution Modes of Pig, Comparison of Pig with Databases, Grunt, Pig Latin, User Defined Functions, Data Processing operators
Unit 5: Pig, Hive and HBase Big Data AKTU With Notes | BTech 3rd Year KCS 061· Engineering in One Video· 38 min
Study notes 5 quiz questionsWatch lesson - 11
Apache Hive Architecture and Metastore
Module IV, Hadoop Eco System: Hive : Hive Shell, Hive Services, Hive Metastore, Comparison with Traditional Databases
Apache Hive Introduction & Architecture· Data Engineering· 18 min
Study notes 5 quiz questionsWatch lesson - 12
HiveQL: Tables, Queries and UDFs
Module IV, Hadoop Eco System: HiveQL, Tables, Querying Data and User Defined Functions
Unit 5: Pig, Hive and HBase Big Data AKTU With Notes | BTech 3rd Year KCS 061· Engineering in One Video· 15 min
Study notes 5 quiz questionsWatch lesson - 13
HBase vs RDBMS and Introduction to Big SQL
Module IV, Hadoop Eco System: Hbase : HBasics, Concepts, Clients, Example, Hbase Versus RDBMS, Big SQL : Introduction
Unit 5: Pig, Hive and HBase Big Data AKTU With Notes | BTech 3rd Year KCS 061· Engineering in One Video· 18 min
Study notes 5 quiz questionsWatch lesson - 14
Getting Data into R: Reading Files
Module V, Data Analytics with R: Reading and getting data into R, reading data from files
Learn R From ZERO — Ep. 12: Importing Data in R (Mac + Windows)· Stats with Aaheli· 18 min
Study notes 5 quiz questionsWatch lesson - 15
R Data Structures: Factors, Matrices, Lists, Data Frames
Module V, Data Analytics with R: ordered and unordered factors, arrays and matrices, lists and data frames, Manipulating objects
R objects in Hindi | vector list matrix array factor data frame | R tutorial | Jayesh Umre· EasyExamNotes.com· 29 min
Study notes 5 quiz questionsWatch lesson - 16
Probability Distributions and Statistical Models in R
Module V, Data Analytics with R: probability distributions, data distribution, statistical models in R
Introduction to R: Probability Distributions· DataDaft· 24 min
Study notes 5 quiz questionsWatch lesson - 17
Machine Learning Algorithms in R
Module V, Data Analytics with R: Using Machine learning Algorithms with R
Machine Learning with R | Machine Learning Algorithms | Data Science Training | Edureka· edureka!· 41 min
Study notes 5 quiz questionsWatch lesson
Assignment
Mini Big Data Pipeline: From Hadoop Design to Analysis in R
Less scrolling. More passing.
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Hand-picked video lessons
17 short lessons, each with the best YouTube explanation we could find, trimmed to the part that matters.
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Study notes
17 lessons come with a summary, key points, key terms and takeaways for quick revision.
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Quizzes
85 questions across the course, with the right answer and why, the moment you pick.
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Assignments
1 subject assignments with clear tasks, so you practise what each subject actually asks of you.
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Notebook
Write notes beside the video, stamped with the exact time, and jump back to that moment later.
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Progress that follows you
Completed lessons, quiz scores and where you stopped, saved to your account on every device.
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Live chat
A members-only live chat beside every lesson: doubts, tips, stickers and GIFs with your batch. One ₹19 pass opens every live chat.
The Online MCA live chat. Study together, live.
A live chat right beside the video, shared by everyone studying Online MCA. Ask a Big Data & Analytics using R doubt mid-lesson, share a shortcut, celebrate a finished semester.
- Live chat beside every lesson
- One live chat for all of Online MCA
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- One ₹19 pass opens every live chat
Online MCA live chat
Anyone else finding Big Data & Analytics using R tricky? 😅
Lesson 2 cleared it up for me. Watch it before the quiz
Doing it now, thanks!
Starting Android Programming tonight if anyone wants to go together
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Big Data & Analytics using R: common questions
This subject introduces big data and the Hadoop ecosystem, covering HDFS, MapReduce, Pig, Hive, HBase and Big SQL, followed by data analysis and machine learning in R. After it you will be able to store and process large datasets on Hadoop, query them with Pig and Hive, and load, explore and model data in R. It's the Big Data & Analytics using R subject of Online MCA, Semester 3, in 17 lessons: Introduction to Big Data and Big Data Analytics; Hadoop Basics: History, Unix Tools vs Hadoop, Streaming; Hadoop Ecosystem and IBM InfoSphere BigInsights; HDFS Design, Concepts and Command Line; Data Ingestion with Flume, Sqoop and Hadoop Archives; Hadoop I/O: Compression, Serialization and Avro; Anatomy of a MapReduce Job Run and Failures; MapReduce Shuffle, Sort and Task Execution; MapReduce Types, Formats and Features; Apache Pig and Pig Latin Tutorial; Apache Hive Architecture and Metastore; HiveQL: Tables, Queries and UDFs; HBase vs RDBMS and Introduction to Big SQL; Getting Data into R: Reading Files; R Data Structures: Factors, Matrices, Lists, Data Frames; Probability Distributions and Statistical Models in R; Machine Learning Algorithms in R.
Yes. Every video lesson is free to watch without an account. A free login unlocks study notes, quizzes, the assignment, a notebook and progress that syncs across devices.
About 5h 58m of video across 17 lessons, plus time for notes and quizzes. Go at your own pace; your place is saved.
Yes: “Mini Big Data Pipeline: From Hadoop Design to Analysis in R”. It comes after the last lesson, with a brief, clear tasks and how the work is judged.
A members-only live chat beside the video, shared by everyone studying Online MCA, where learners ask doubts, share tips and react with stickers and GIFs. One ₹19 pass, paid once from your InsideEdge wallet, opens the live chat for every degree.
No. It's a crash course to help you understand and revise the subject quickly. Use it alongside your official study material and assignments.