Introduction
Course Content
Instructor
Schedule
Introduction
Course Content
Instructor
Schedule
Introduction

According to the latest TIOBE Programming Community Index (a software quality comapany), Python
is one of the top 10 popular programming languages of 2017. Python is a general purpose and high
level programming language. You can use Python for developing desktop GUI applications, websites
and web applications. Also, Python, as a high level programming language, allows you to focus on
core functionality of the application by taking care of common programming tasks. The simple
syntax rules of the programming language further makes it easier for you to keep the code base
readable and application maintainable.

Course Content

Week 1

Introduction to the Python Programming

How to Use the Interactive Textbook

Values and Data Types

Operators and Operands

Data Types

Type Conversion Functions

Variables

Statements and Expressions

Hard-Coding

 

 

Week 2

Introduction to Objects and Turtle Graphics

Importing Modules

Introduction to Debugging

Syntax, Runtime, and Semantic Errors

Incremental Programming

 

 

Week 3

Introduction to Sequence Mutation

Concatenation and Repetition Programming

Logical Operators

Unary Selection, Nested Conditionals, and Chained Conditionals

The Accumulator Pattern with Conditionals and Accumulating a Maximum Value

 

 

Week 4

Introduction to Methods on Lists and Strings

Methods on Lists

Non-Mutating Methods on String

 

 

Week 5

Introduction to Accumulating Lists and Strings

The Accumulator Pattern with Lists

The Accumulator Pattern with Strings

Accumulator Pattern Strategies

 

 

Week 6

Introduction to Python Classes and Inheritance

Adding Parameters to the Constructor

Creating Instances from Data

Special (dunderscore) Methods

Sorting Lists of Instances

Class Variables and Instance Variables

 

 

Week 7

Inheriting Variables and Methods

Overriding Methods and Types

Invoking the Parent Class's Method

 

 

Week 8

Introduction toTest Cases

Side Effect Tests

Program Development with Test Cases

Testing Classes

 

 

Week 9

Exception Handling Flow-of-control

When to use Try/Except

Handling Different Exception Types

 

 

Week 10

Introduction to Python Frameworks

Working with Django

How Django Uses Classes and Inheritance

Working on Django project

 

 

Week 11

Introduction to Python Functions, Files, and Dictionaries

Handling files with Python in File System

Programming with CSV files

 

 

Week 12

Introduction to Dictionaries

Dictionary Operations

Dictionary Methods

Dictionary Accumulation

 

 

Week 13

Introduction to File Handling Functions

Positional Parameter Passing

Variable Scoping

Mutable Objects and Side Effects

 

 

Week 14

More Iteration and Advanced Functions

 

 

Week 15

Introduction to Nested Data

Nested Dictionaries

JSON Format and the JSON Module

Structuring Nested Data

 

 

Week 16

Introduction to  Map and Filter

Map Programming

Filter Programming

 

 

Week 17

Introduction to List Comprehensions

List Comprehensions Projects

The Hangman Blanked Function

 

 

Week 18

Introduction to REST APIs

How the Internet Works

REST API URL

The requests Module

Using REST APIs in Pythons Porjects

Caching Response Content

 

 

Week 19

Rest API Proeject

 

 

Week 20

Intro to Qwiklabs

Projects on Qwiklabs

 

 

Week 21

Introduction to TensorFlow

TensorFlow API Hierarchy

Graph and Session

Visualizing a graph

 

 

Week 22

Scaling TensorFlow models

Cloud AI Platform

Monitoring and Deploying Training Jobs

Scaling TensorFlow with Cloud AI Platform

 

 

Week 23

Tensor Flow Project

 

 

Week 24

FYP Project

Instructor
Schedule

Class Days: Monday - Friday

Class Timings: 09:00AM - 02:00PM

Introduction

In this Course students will learn basic understanding of biology concepts, designs, development/coding, testing and installation are the basic steps for bioinformatics application development.

Objectives of the Course


The objective of the course is to train the person in such a way so that he/she may be able to learn and understand the advanced technologies and terminologies of bioinformatics as well as develop tools/software in this domain.

Competencies gained after completion of course
By the end of this course, the trainees should gain the following competencies:
• Understanding of sequencing technologies
• Central dogma and phylogenetics
• Design and structure of bioinformatics databases
• Design and coding skills
• Disease oriented genes, their structure and visualization

Course Content

Module 1: Introduction to bioinformatics and it’s application
Module 3: Sequence alignments
Module 4: Phylogenetics
Module 5: Ontologies and HMM implementation
Module 6: R and Python programming 
Module 7: Gene Pathways and network analysis 
Module 8: Regulatory Network analysis and data representation 
Module 9: Genome contamination, mutation and variation 
Module 10: Disease and cancer genomics
Module 11: Clinical Data understanding and survival analysis 
Module 12: Disease Hallmarks and cloud computing
Module 13: Metagenomics and biomarkers 
Module 14: Drug discovery pipeline

Instructor
Schedule

Class Days: Monday - Friday

Class Timings: 04:00PM - 09:00PM