Learn Hadoop and BigData Technologies

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Get more out your data and learn to master big data with our Hadoop and Big Data Technologies online training course.

💓 Price : FREE

📝 Lectures: 76

📺 Video: 15.5 hours

📱 Level: All level

💼Languages: English

Hadoop Online Course contains over 74 lectures & 15.5 hours of content, at the end of the course you would become a complete Hadoop, Map Reduce and Bid Data Professional. The course is designed for IT professionals and managers who want to understand and learn Hadoop, Big Data and Map Reduce Online

Big Data & Hadoop training Course is designed to provide knowledge and training Online to be a complete hadoop professional by learning hadoop online, An indebt knowledge of Hadoop Core concepts like Map reduce training and Learning Big Data would also be provided.

Course Content : 

Section 1 : Introduction to Big Data

1 Introduction to the Course

2 Why Hadoop, Big Data and Map Reduce Part - A

3 Why Hadoop, Big Data and Map Reduce Part - B

4 Why Hadoop, Big Data and Map Reduce Part - C

5 Architecture of Clusters

6 Virtual Machine (VM), Provisioning a VM with vagrant and puppet

 Section 2 : Hadoop Architecture

7 Set up a single Node Hadoop pseudo cluster Part - A

8 Set up a single Node Hadoop pseudo cluster Part - B

9 Set up a single Node Hadoop pseudo cluster Part - c

10 Clusters and Nodes, Hadoop Cluster Part - A

11 Clusters and Nodes, Hadoop Cluster Part - B

12 NameNode, Secondary Name Node, Data Nodes Part - A

13 NameNode, Secondary Name Node, Data Nodes Part - B

14 Running Multi node clusters on Amazons EMR Part - A

15 Running Multi node clusters on Amazons EMR Part - B

16 Running Multi node clusters on Amazons EMR Part - C

17 Running Multi node clusters on Amazons EMR Part - D

18 Running Multi node clusters on Amazons EMR Part - E

Section 3 : Distributed file systems

19 Hdfs vs Gfs a comparison

20 Run hadoop on Cloudera, Web Administration

21 Run hadoop on Hortonworks Sandbox

22 File system operations with the HDFS shell Part - A

23 File system operations with the HDFS shell Part - B

24 Advanced hadoop development with Apache Bigtop Part - A

25 Advanced hadoop development with Apache Bigtop Part - B

Section 4 : Mapreduce Version 1

26 MapReduce Concepts in detail Part - A

27 MapReduce Concepts in detail Part - B

28 Jobs definition, Job configuration, submission, execution and monitoring Part -A

29 Jobs definition, Job configuration, submission, execution and monitoring Part -B

30 Jobs definition, Job configuration, submission, execution and monitoring Part -C

31 Hadoop Data Types, Paths, FileSystem, Splitters, Readers and Writers Part A

32 Hadoop Data Types, Paths, FileSystem, Splitters, Readers and Writers Part B

33 Hadoop Data Types, Paths, FileSystem, Splitters, Readers and Writers Part C

34 The ETL class, Definition, Extract, Transform, and Load Part - A

35 The ETL class, Definition, Extract, Transform, and Load Part - B

36 The ETL class, Definition, Extract, Transform, and Load Part - C

37 The UDF class, Definition, User Defined Functions Part - A

38 The UDF class, Definition, User Defined Functions Part - B

Section 5 : Mapreduce with Hive ( Data warehousing )

39 Schema design for a Data warehouse Part - A

40 Schema design for a Data warehouse Part - B

41 Hive Configuration Part A

42 Hive Configuration Part B

43 Hive Query Patterns Part - A

44 Hive Query Patterns Part - B

45 Hive Query Patterns Part - C

46 Hive Query Patterns Part - D

47 Example Hive ETL class Part - A

48 Example Hive ETL class Part - B

49 Example Hive ETL class Part - C

Section 6 : Mapreduce with Pig (Parallel processing)

50 Introduction to Apache Pig Part - A

51 Introduction to Apache Pig Part - B

52 Introduction to Apache Pig Part - C

53 Introduction to Apache Pig Part - D

54 Pig LoadFunc and EvalFunc classes

55 Example Pig ETL class Part - A

56 Example Pig ETL class Part - B

Section 7 : The Hadoop Ecosystem

57 Introduction to Crunch Part - A

58 Introduction to Crunch Part - B

59 Introduction to Avro

60 Introduction to Mahout Part - A

61 Introduction to Mahout Part - B

62 Introduction to Mahout Part - C

Section 8 : Mapreduce Version 2

63 Apache Hadoop 2 and YARN Part - A

64 Apache Hadoop 2 and YARN Part - B

65 Yarn Examples

Section 9 : Putting it all together

66 Amazon EMR example Part - A

67 Amazon EMR example Part - B

68 Amazon EMR example Part - C

69 Amazon EMR example Part - D

70 Apache Bigtop example Part - A

71 Apache Bigtop example Part - B

72 Apache Bigtop example Part - C

73 Apache Bigtop example Part - D

74 Apache Bigtop example Part - E

75 Apache Bigtop example Part - F

76 Course Summary

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