360 Data Science

₹25,000.00

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360o Data Science

Get started into a Data Science career with a comprehensive program designed and developed by experts with over 15 years of industry experience.
Avail at as less as ₹ 25,000/-

Call Now
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360 Data Science

Get started into a Data Science career with a comprehensive program designed and developed by experts with over 15 years of industry experience.
Avail at as less as ₹ 25,000/-

Call Now
Whatsapp

Key Highlights

No programming experience required.
Training on Data Engineering, Analytics, Machine Learning, Neural Nets and Visualization.
Designed for learners from all backgrounds.
Get job-ready in multiple areas of Data Science.
Career assistance programs for all learners.
Mentored more than 2000+ learners on Data Science and Analytics.
Adaptive learning plans with classes available online or in-class.

Course Includes

1 Big Data with Hadoop


• Big Data and its Sources
• RDBMS vs. Hadoop
• Hadoop Architecture and Ecosystem
• When to Use and Not use Hadoop
• HDFS Characteristics and Definitions
• HDFS Design and Architecture Overview
• Accessing HDFS
• HDFS Commands
• Basic File System Operations
• HDFS Administration Commands
• HDFS Features and Benefits

2 R Programming


Introduction to R
• Math, Variables, and Strings
• Vectors and Factors
• Vector operations

Data structures in R
• Arrays & Matrices
• Lists
• Data frames

R programming fundamentals
• Conditions and loops
• Functions in R
• Objects and Classes
• Debugging

Working with data in R
• Reading CSV and Excel Files
• Reading text files
• Writing and saving data objects to file in R

Strings and Dates in R
• String operations in R
• Regular Expressions
• Dates in R

3 Machine Learning For Data Science & Analytics

Machine learning vs. Statistical modelling

Supervised vs. Unsupervised Learning
• Machine Learning Languages, Types, and Examples
• Machine Learning vs Statistical Modelling
• Supervised vs Unsupervised Learning
• Supervised Learning Classification
• Unsupervised Learning

Supervised Learning
• Understanding nearest neighbour classification
• The KNN algorithm
• Measuring similarity with distance
• Choosing Appropriate K
• Use Case

Classification Using Naïve Bayes
• Basic Concepts of Bayesian Methods
• Probabilistic Learning

Classification using Decision Trees
• The C5.0 decision tree algorithm
• Understanding Classification Rules
• Separate and Conquer
• Rules from decision trees
• Advantages & Disadvantages of Decision Trees

Understanding Regression
• Simple Linear Regression
• Ordinary least Square estimation

Correlations

Multiple Linear Regression

Support Vector Machines
• Classification with Hyper planes
• Using Kernels for non-linear spaces

Neural Networks
• Black Box Methods
• Training neural networks with back propagation

Unsupervised Learning

Association Rules – Pattern detection
• K-Means Clustering plus Advantages & Disadvantages
• Hierarchical Clustering plus Advantages & Disadvantages
• Measuring the Distances Between Clusters – Single Linkage Clustering
• Measuring the Distances Between Clusters – Algorithms for Hierarchy Clustering
• Density-Based Clustering

Evaluating Model Performance

Improving Model Performance

4 Data Visualization with Tableau

Introduction to Tableau Desktop

Connecting to Data

Customizing a Data Source
• Filtering Your Data
• Sorting Your Data
• Creating Groups in Your Data
• Creating Hierarchies in Your Data
• Working with Date Fields: Discrete and Continuous Time
• Working with Date Fields: Custom Dates
• Working with Multiple Measures: Dual Axis and Combo Charts
• Working with Multiple Measures: Combined Axis Charts
• Showing Relationships between Numerical Values
• Mapping Data Geographically
• Using Crosstabs: Totals and Aggregation

Using Crosstabs: Highlight Tables
• Using Crosstabs: Heat Maps
• Using Calculations: Customize Your Data
• Using Calculations: Working with Strings, Dates, and Type Conversion Functions
• Using Calculations: Working with Aggregations
• Using Quick Table Calculations to Analyze Data
• Showing Breakdowns of the Whole
• Highlighting Data with Reference Lines
• Create a Dashboard: Combining Your Views
• Create a Dashboard: Add Actions for Interactivity
• Sharing Your Work

Working with a Data Extract
• Joining Tables
• Blending Multiple Data Sources
• Blending Data without a Common Field
• Using Split and Custom Split
• Advanced Calculations: Aggregating

Dimensions
• Controlling Table Calculations
• Showing the Biggest and Smallest Values
• Using Level of Detail Expressions
• Filtering and LOD Expressions
• Using Parameters to Control Data in the View
• Parameters: Swap Measures

Using Sets to Highlight Data
• Advanced Mapping: Modifying Locations
• Advanced Mapping: Customizing Tableau’s Geocoding
• Advanced Mapping: Using a Background Image
• Viewing Distributions
• Comparing Measures Against a Goal
• Showing Statistics and Forecasting: Use the Analytics Pane and Trend Lines Advanced

Dashboards: Using Design Techniques and Filter Actions

Telling Stories with Data

5 Python Programming

Python Programming
Introduction to python
• Python History
• Python History
• Python Applications

Installation Setup and Testing
• Python Install
• Python Path
• Python Example
• Execute Python

Datatypes, declarations and comments
• Python Variables
• Python Data Types
• Python Keywords
• Python Literals
• Python Comments

Operators in Python
• Arithmetical Operators
• Relational Operators
• Logical Operators
• Assignment operators

Conditional Statements
• Simple IF
• If and Else
• Nested If

Python Loops
• Python for loop
• Python while loop
• Python break
• Python continue
• Python pass

Python String handling and functions
• capitalize()
• center()
• count()
• endswith()
• format()
• rjust()
• ljust()
• len()
• replace()
• upper()
• lower()
• split()

Number functions
• abs(), ceil(), floor(), cmp(), exp()
• log(), log10(), min(), max(), power()
• round(), sqrt()

Date Functions
• import datetime module
• now()
• datetime()
• import calendar
• calender.month()
• calendar.prcal(2019)
• import time
• time.time() and more functions followed

Python Collections
• Python Lists
• Python Tuples
• Python Sets
• Python Dictionary

Python user define Functions
• Using def keyword to define function
• Function with return keyword
• Function with argument
• Python Lambda Functions

6 Advance Python Programming

Advance Python Programming
File Handling in Python
• Python Files I/O
• create file using “r”, “w” ,”a” modes
• Python Modules

Python Exceptions
• Types of Exceptions in python
• using try, except keyword
• else usage in exception handling
• usage of finally keyword
• user defined exceptions

Python OOPs
• Python OOPs Concepts
• Python Class designing
• Object creation and handling class properties through object
• Python Constructors and overloading of constructor
• Method overloading in class
• Python Inheritance with single multi-level and Hierarchy
• Python interfaces and implementation Python with database
• configure database
• connecting to Oracle
• connecting to Mysql
• adding mandatory plugins
• CRUD operations in Python with Database

Python OS module
• create folder
• remove folder
• rename file
• host os command

Python network concept
• Client socket
• Server socket

Threading program in Python
• What is threading
• Activation of thread
• Life cycle of thread
• Thread processing in python

7 Django For Web Development With Python

Django for Web Development with Python
Django Introduction
• Django Features
• Rapid Development
• Secure
• Scalable
• Fully loaded
• Versatile
• Open Source
• Vast and Supported Community

Django Installation
• Install Django using pip command
• Verify installation using import django over shell

Django Project
• Creation of django project
• Locate project
• Run django project
• Apache Configuration
• Virtual Environment Setup
• Admin Interface
• Django App

Django MVT
• Django Model
• Django View
• Django Template
• URL Mapping
• Static Files Handling

Form handling
• Model Forms
• Django Forms
• Form Validation
• File Upload Database with Django
• Database Connectivity
• Database Migrations
• Django Middleware
• Request and Response
• Django Exceptions

Session Tracking
• Django Session
• Django Cookie

External File Output creation using Django
• Django CSV Output
• Django PDF Output
• Django and Bootstrap

Additional Features of Django
• Deploy on Github
• Django Mail Setup
• Django Default CRUD
• CRUD Application

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