Report File- 5 Days FDP on “Demystifying the Data”

Organized by

Report File – 5 days Online FDP on Demystifying the Data Organized by – LNJPIT ,Chapra in Collaboration with

Splen Technologies

Report File – 5 Days FDP on “Demystifying

the data”

LNJPIT , Chapra, Invites the Computer Science and IT Faculties from All the Institutes to

attend the 5 Days workshop on Demystifying the Data which unique blend of Data Science,

ML , Big Data and AI in collaboration with Splen Technologies

Day 1-

Session 1-

Agenda /

Topics

Session 1-

1- Introduction to the Field of Data

Science 2- Importance of Data

3- Introduction to the Verticals of Big Data

analytics 4- Introduction to the Frame work of

Big Data

5- Hands on Guide on Framework such as Hadoop ,Pig ,Appache , Spark

Session 2-

The step to a Data Scientist is the ability to work with Big Data and its components.

This training is deep dive into Hadoop and all its ecosystem components including

MapReduce, HDFS, Yarn, HBase, Impala, Sqoop and Flume.

1- Introduction to Bigdata and Hadoop Ecosystem

2- HDFC and Hadoop Architecture: Learn about HDFS architecture and

components like Block replication architecture in this lesson MapReduce and Sqoop:

Know the importance of Map Reduce, data types in

3- Map Reduce, joins in Map reduce, and Sqoop Basics of Impala and Hive:

Introduce yourself to the Basics of Impala and Hive and learn how to interact with

them

4- Type of Data Formats: Gain Knowledge of data Types in Hive, Hcatalog, and Its uses

Know what is data Serialization, how to import MySql and Create hivetb,

Parquet With Sqoop in this lesson.

Day 2-

Session 1-

Agenda /

Topics

● What is Big Data & its Challenges ?

● How Apache Hadoop deal with Big Data?

● Hadoop Ecosystem Introduction.

● Industries Use Cases & PoC

● Hands-on Apache PIG | Apache Flume & HDFS

Session 2-

Agenda / Topics

–

● Hadoop Testing Career - Who can go for it.

● Hadoop Career - Salary & Industry Outlook

● Organization having Jobs In Hadoop.

● Real Time Demonstration of Code.,Hands on Session

Day 3-

Session 1-

Topics /

Agenda-

Introduction to

tableau Connecting

datasets

Tableue Interface

description Frame

Filter

Hands on

Session 2-

Tableaue

Application Quiz

Set

Hands on Programming

1- Introduction to Map Reduce Programming

2- Developing the Industry Oriented Projects Using

Hadoop 3- Hands on Practical Session

Day 4-

Session 1-

Topics / Agenda –

1-Recap of Beginners Python This module will focus on a revision of: Data types,

Sequences, Mapping types, Program structure, Files and console I/O, Conditionals,

Loops and Bulletins 2- Hands on Programming Session

3- Implementation on Live

Projects 4- Introduction to

Python Pandas

5- Hands on Programming Session

Session 2-

1- Introduction to the NumPi

2- Introduction to Plythonic Programming

3- Introduction to the Network

Programming 4- Introduction to the

lambda function

5- Hands on Programming Session

6- Python Requires for the Journey of Data Science ,ML

Day 5- After Recap of the previous session -

1- Beginning the Journey in the Field of Data Analysis

2- Data Science Overview: Get introduced to Data Science, dierent sectors

using Data Science, and purpose and components of Python

3- Python Environment Setup and Essentials: Learn how to install Anaconda

Python Distribution, basic operators, data types, and functions

4- Mathematical Computing with Python (NumPy): Overview of Numpy, Class and

Attributes of ndarray

5- Revision Session

Session 2-

Topics/Agenda

–

1- Introduction to Artificial Intelligence and Machine Learning: Get introduced to

Machine Learning concepts, logarithms, and its applications

2- Techniques of Machine Learning: Learn about supervised, unsupervised, semi-

supervised, and reinforced machine learning techniques

3- Introduction to Deep Learning: Understand the meaning and importance of deep learning,

Artificial Neural networks, and TensorFlow4- Math Refresher: Overview of Linear Algebra,

Eigenvalues, Eigenvectors, and Eigendecomposition, Calculus, Probability and Statistics

Regression: Know Linear Regression:

Equations and Algorithms in this lesson

5- Revision Session and Hands on and quiz

Feedback /Suggestion /Query

Faculties Participated -43

Colleges –

Delivery Methodology Opted By the

Mentor Excellent -76.7%

Good – 23.3%

Subject Knowledge level of mentor

Excellent -

72.1% Good-

27.9%

Was this workshop

Fruitful- Yes – 100%

No-0%

Visualisation and Presentation of this FDP

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in other such fdp and workshop

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