Data Science and Machine Learning - L & D Edutech

+91 72087 69880 info@landdedutech.com

Data Science and Machine Learning

Data Science using Python& R Programming

(Duration : 3months)

Module 1 : Overview of Data Science

Introduction to Data Science
Use Cases
The need for Business Analytics
Data Science Life Cycle
Different tools available for Data Science

Module 2 : R Programming

Introduction to R Programming
Installing R and R-Studio
R packages and R Operators
if statements and loops (for, while, repeat, break, next), switch case.

Module 3 : Python Programming

Introduction to Python
Installation and working with Python
Understanding Python variables
Python Operators
Python blocks

Flow Control Conditional blocks using if, else and elif
Simple for loops in python
For loop using ranges, string, list and dictionaries
Use of while loops
Loop manipulation using pass, continue, break and else
Programming using Python conditional and loops block

Module 4: Data Types

Declaring and using Numeric data types
Using String data type and operations
Defining List
Use of Tuple data type

Module 5 : Functions, Modules & Packages

Organizing python codes using functions
Organizing python projects into modules
Importing own module & external modules
Understanding Lamda function in python
Programming using functions, modules and external packages

Module: 6 String, List & Dictionary

Building blocks of python programs
Understanding String in-build methods
List manipulation using in-build methods
Dictionary manipulation
Programming using String, List and Dictionary in-build functions

Module: 7 File Operation

Reading config files in python
Writing log files in python
Understanding read functions, read(), readline() and readlines()
Understanding write functions, write() and writelines()
Manipulating file pointer using seek Programming using file operations

Module: 8 Object Oriented Programming

Concept of class, object and instances
Constructor, class attributes and destructors
Inheritance, Overlapping and Overloading operators
Adding and retrieving dynamic attributes of classes

Module: 9 Regular Expression

Pattern matching and searching
Pattern searching using regex, real time parsing of data using regex
Password, email, url validation using regular expression

Module: 10 Exception Handling

What is exception handling
Safe guarding file operation using exception handling
Handling error code
Programming using Exception handling

Module: 11 Multithreading

Understanding threads
Forking threads
Synchronizing the threads

Advanced Python

Module 1: Overview

Python Iterators
Python Generators
Python Closures
Python Decorators
Python @property

Module: 2 Python XML & JSON parser

What is XML?
Difference between XML and HTML
Difference between XML and JSON
How to Parse XML
How to write XML
How to parse JSON
How to write JSON

Module : 3 Python Data Communication

Creating a Database with SQLite 3,
Creating a Database Object.
Python MySQL Database Access
DML and DDL Operations with Databases
Performing Transactions
Handling Database Errors
Disconnecting Database

 Introduction To Machine Learning With Python (Including Project)

Module: 1 Introduction to Machine Learning

What is Machine learning?
Machine Learning Methods
Predictive Models
Descriptive Models
What are the steps used in Machine Learning?

Module: 2 Regression

Simple Linear Regression
Multiple Linear Regression
Bias-Variance trade-off

Module: 3 Classification

Logistic Regression
K-Nearest Neighbors (K-NN)
SVM
Decision Trees
Random Forest

Module: 4 Clustering

K-means
Hierarchical
DBSCAN

Module: 5 Dimensionality Reduction

Linear discriminant analysis
Principal component analysis

Soft Skills& Interview Techniques

Interview Techniques
Frequently Asked Questions
Group Discussion
Resume Writing
Mock Test Based on MNC Test Pattern

Evaluation

Technical Assignments
Technical Test
Technical Interview