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Data Science and Big Data Analytics training

Trending in Pune-Data Science and Big Data Analytics training are exciting new areas that combine scientific inquiry, statistical knowledge, substantive expertise, and computer programming.

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Data Science and Big Data Analytics training

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  1. DATA SCIENCE Introduction to Data Science, Use cases, Need of Business Analytics, Data Science Life Cycle, Different tools available for Data Science. 1) R Programming 1.1 Introduction to R 1.2 Installation of R -Windows Installation -Linux Installation Installing R and R-Studio, R packages, R Operators, if statements and loops (for,while, repeat, break, next), switch case 1.3 Types of Datatype -Arrays -Data Frames -Lists -Factors R Data Structure (Vector, Scalar, Matrices, Array, Data frame, List), Functions, Apply Functions 1.4 Types of Variables 1.5 Types of Operators -Arithmetic operator -Logical Operator -Relational Operator

  2. 1.6 Types of control statements: -If statement -If else statement -if else if statement -switch statement 1.7 Types of Loops : -for loop -while loop -nested loop 1.8 Function Declaration -Function declaration with parameters -Function declaration without parameters 1.9 R Data Interface 1.10 R Charts and Graphs -Pie Chart -Bar chart -Line graph 1.11 R statistics Terminologies of Statistics ,Measures of Centres, Measures of Spread, Probability, Normal Distribution, Binary Distribution 1.12 Machine learning algorithms -classification the act or process of classifying -clustering form a cluster or clusters. -regression a return to a former or less developed state.

  3. 2)PYTHON 1.1 Introduction to Python - What is Python and history of Python? -Unique features of Python -Python-2 and Python-3 differences -Install Python and Environment Setup -First Python Program -Python Identifiers, Keywords and Indentation -Comments and document interlude in Python -Command line arguments -Getting User Input -Python Data Types -What are variables? -Python Core objects and Functions -Number and Maths -Week 1 Assignments 1.2 List, Ranges & Tuples in Python -Introduction to list, tuples, ranges -Lists in Python -More About Lists -Understanding Iterators

  4. -Generators,Comprehensions Expressions - Introduction to generators,yields and Lambda -Generators and Yield -Next and Ranges -Understanding and using Ranges -More About Ranges -Ordered Sets with tuples 1.3 Python Dictionaries and Sets -Introducing to the section -Python Dictionaries -More on Dictionaries - Introducing to Sets -Python Sets Examples 1.4 Input and Output in Python -Reading and writing text files -writing Text Files -Appending to Files and Challenge -Writing Binary Files Manually -Using Pickle to Write Binary Files 1.5 Python built in function

  5. -Python packages functions(Numpy,Pandas,Scipy) -Defining and calling Function -The anonymous Functions - Loops and statement in Python -Python Modules & Packages 1.6 Python Object Oriented - Formal presentation of object oriented programming -Topping up topics like: Abstraction Encapsulation, Inheritance, Polymorphism, -Creating Classes and Objects -Accessing attributes -Built-In Class Attributes -Destroying Objects 1.7 Python Exceptions Handling -What is Exception? -Handling an exception -try….except…else -try-finally clause -Argument of an Exception

  6. -Python Standard Exceptions -Raising an exceptions -User-Defined Exceptions 1.8 Machine learning algorithms -classification -the act or process of classifying -clustering form a cluster or clusters. -regression a return to a former or less developed state.

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