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A process of inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusion and supporting decision-making.The journey of making millions of raw data become valuable is the job of a data scientist.

Python Programming master class

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Fundamentals

Python Programmin Masterclass

Intermediate

Big Data and Analytics

Advanced

Artificial Intelligence for Data Analytics

Proposed modules
  1. 1
    Python Programmin Masterclass

    Day 1
    • History of Programming
    • Programming basics
    • Why program with Python
    Day 2
    • Introduction to Python
    • Python – First Python program
    • Python – Understanding Data Types
    • Python – Working with Strings
    Day 3
    • Python – Understanding variables
    • Python – Math Operators and Boolean logic
    Day 4
    • Python – Understanding Lists
    • Python – List Methods
    Day 5
    • Python – Understanding Tuples
    • Python – Understanding Dictionaries
    • Python – modules
    Day 6
    • Python – modules (creating modules)
    • Python – Conditional Statements
    • Python – While Loops
    Day 7
    • Python – For Loops
    • Python – More loops
    • Python – Functions
    Day 8
    • Python – Using *args and **kwargs
    • Python – Classes and Objects
    • Python – Understanding Classes and instance variables
    Day 9
    • Python – Understanding Inheritance
    • Python – Applying Polymorphism to classes
    • Python – debugging
    Day 10
    • Python – interactive console
    • Python Best practices

  2. 2
    Big Data and Analytics

    Day 1
    • 1.Introduction to Big Data and Hadoop
    • 2.Hadoop Architecture Distributed Storage (HDFS) and Yarn
    • 3.Data Ingestion into Big Data Systems and ETL
    Day 2
    • 4.Distributed Processing MapReduce and Pig
    • 5.Apache Hive
    • 6.HBase NoSQL database
    Day 3
    • 7.Basics of functional programming and SCALA
    • 8.Apache Spark
    • 9.Spark Core Processing RDD
    Day 4
    • 10.Spark SQL Processing DataFrames
    • 11.SparkMLLib modelling BigData with Spark
    • 12.Stream Processing Frameworks and Spark Streaming
    Day 5
    • 13.Spark GraphX
    • 14.Alternate Graph engines
    • 15.Neo4j Introduction
    Day 6
    • 16.Neo4j Cypher
    • 17.Neo4j Graph Analytics

  3. 3
    Machine Learning and Artificial Intelligence for Data Analytics

    Day 1
    • Introduction to Artificial Intelligence
    • Python in Artificial Intelligence

    Day 2
    • Data Visualization
    • Data Analytics

    Day 3
    • Data Exploration

    Day 4
    • Supervised Learning
    • Supervised Learning Classification
    • Unsupervised Learning

    Day 5
    • Developing a Machine Learning model

    Day 6
    • Deploying a machine learning solution

Participants will be evaluated based on project work and multiple-choice questions.

  • Python
    • Application Development Project
    • 50 multiple choice and true/false questions. Closed book.

    Duration – 2 hours.
    Passing Rate – 65%

  • Big Data
    • Big Data Development Project
    • 50 multiple choice and true/false questions. Closed book.

    Duration – 4 hours.
    Passing Rate – 65%

  • Artificial Intelligence
    • AI Model Development Project
    • 50 multiple choice and true/false questions. Closed book.

    Duration – 4 hours.
    Passing Rate – 65%

Yes I’m Interested

    CCSD’s focuses on driving the digital agenda via certifying working professionals in key IR4 related skills upon assessing them , digital quotient for corporates and governments and digital skills.

    ADDRESS

    Belehradska 858/23 Prague 2, 120 00,
    Ccsd council s.r.o

    PHONE

    for APAC:+60 16-912 3051 
    Working Hours - 9:00AM - 5:00PM (SST)

    for Other Countries:+420733337965
    Working Hours - 9:00AM - 5:00PM (CET)

    EMAIL

    info@ccsdcouncil.org
    admin@ccsdcouncil.org

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