Introduction

“Big Data” is a collection of data that have huge volume, fast velocity, and/or high variety information assets that require new forms of procession to enable enhanced decision making, insights discovery and process optimization”

Big Data is a Revolution, a way to solve all the unsolved problems related to data management and handling. While earlier industry used to live with such problems, big data analytics unlock hidden patterns and provide a 360-degree view of customers to better understand their needs. This course will provide you with a strong foundation in analytics, tools, and statistics. It will help you use data analytics, big data, and predictive analytics to optimize performance in fields like data analytics, big data analytics, programming, and more. It will provide you with the necessary credentials you need to positively influence the decision-making processes.

Duration

5 days

COURSE LEVEL: Intermediate

Course Objectives

This course will teach you how to perform common data science tasks such data wrangling, visualization, and building machine learning models in Python. This course takes a practical approach to equip participants with the most essential tools in the shortest possible time. The course emphasizes learning by doing as such they are a lot of exercises built into the course to give participants ample time to practice. In addition, you will learn the powerful of CLI, Hadoop as big data solution, and more!

Module 1: Introduction to Big Data analytics

• Python for Big Data analytics
  • Installing Python and its necessary modules
  • Setting up working environment
  • Basic Operation
    • Import module
    • For and While loops
    • Functions, IF, ELIF, and ELSE
  • Working with data frame
    • Reading a data frames from csv or excel files
    • Reading a data frame from RDBM table
    • Manipulating the data frame
    • Writing data frame to disk as csv file

Module 2: Data visualization and Insights discovery

• Data visualization
  • Create Bar chart
  • Create Pie chart
  • Create Scatter chart

• Pattern discovers on small data
  • Combined line charts
  • Time Series data analytics
• Statistical analysis on small data
  • Descriptive statistics on a loaded data frame
  • Sampling techniques with practices
  • Box-plot chart to identify the outliers

Module 3: Machine Learning and its Application

• What is Machine Learning?
• Machine Learning Use-Cases for data science
  • Data Cleaning
  • Data Pre-Processing
  • Classification
  • Regression
  • Forecasting the future using Facebook prophet

Module 4: Big Data Tools

• Introduction to Command Line Interface (CLI)
  • Folders structure
  • Navigate, Create, Delete folders
  • Reading file’s contents
  • Copy, Cut, Past files
  • Networking commands
    • Ipconfig/Ifconfig
    • Ping
    • Arp-a

• Hadoop as Big Data Management Solution
  • Installation and configuration
    • Data node (master)
    • Name nodes (slaves)
  • HDFS in real-life problems
    • Importing local files to Hadoop HDFS
    • Importing local relational databases to Hadoop HDFS using Sqoop in Hive
    • Storing NoSQL DBs in Hbase, Hbase is a NoSQL database built on top of Hadoop (HDFS, to be exact)
  • MapReduce
    • Parallel processing

Module 5: Big Data Solution on Business Intelligence

• Apache spark for big data fast processing solution
  • Install spark in python
  • Read the data frame using spark
• Introduction to Cloud Computation as big data solution
  • Google colab
  • IBM cloud, and more
• Connecting business intelligence tools (PowerBI, and more) to big data architectures for reporting.

The way the BI tools can be connected to the relational databases is the same way we connect to HDFS, here we use Hive instead of RDBM. We use the master machine credentials and its IP address to access the databases stored in HDFS. We use the adapters as we normally do to connect to the RDBM. This is done by:

• Identifying the server connection credentials
• Identifying the data we need to report
• Linking live dashboards to big data architectures

Course Administration Details:

METHODOLOGY

The instructor led trainings are delivered using a blended learning approach and comprise of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.

All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.

ACCREDITATION

Upon successful completion of this training, participants will be issued with an Indepth Research Institute (IRES) certificate certified by the National Industrial Training Authority (NITA).

TRAINING VENUE

The training will be held at IRES Training Centre. The course fee covers the course tuition, training materials, two break refreshments and lunch.

All participants will additionally cater for their, travel expenses, visa application, insurance, and other personal expenses.

ACCOMMODATION AND AIRPORT PICKUP

Accommodation and airport pickup are arranged upon request. For reservations contact the Training Officer.

Email:[email protected]/[email protected]

Mob: +254 715 077 817/+250789621067

TAILOR- MADE

This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our IRES Training Centre or at a convenient location.

For further inquiries, please contact us on Tel: +254 715 077 817/+250789621067

Mob: +254 792516000, +254 792516010 , +250 789621067 ,or mail [email protected]/[email protected]

PAYMENT

Payment should be transferred to IRES account through bank on or before start of the course.

Send proof of payment to [email protected]/[email protected]

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