Data Science Python Online Course in Bangalore | India

Data Science using Python

This course will provide detailed hold on different packages and libraries needed for data analysis, data visualization, machine learning, web scrapping with the base of Python. The main topical aspects for this course would be getting held up with strong hold on Python and Advanced data analytics techniques.

16,015 15,025

Courses Description

This course will provide detailed hold on different packages and libraries needed for data analysis, data visualization, machine learning, web scrapping with the base of Python. The main topical aspects for this course would be getting held up with strong hold on Python and Advanced data analytics techniques.

  • Fundamentals on Python
  • Conceptualization on Data Science such as Data exploration/pre-processing/ Mugging etc
  • Usage of Python in ML
  • Courses Curriculum

    Lecture1.1 Data science & its importance

    Lecture1.2 Key Elements of Data Science

    Lecture1.3 Data Warehousing

    Lecture1.4 Business Intelligence

    Lecture1.5 Data Visualization

    Lecture1.6 Data Mining

    Lecture1.7 Machine Learning

    Lecture1.8 Artificial Intelligence

    Lecture1.9 Cloud Computing

    Lecture1.10 Big Data

    Lecture1.11 Artificial Intelligence: A preview

    Lecture1.12 What is Artificial Intelligence & its importance

    Lecture1.13 Artificial Intelligence vs Machine Learning

    Lecture2.1 Numpy

    Lecture2.2 2D Numpy Array

    Lecture2.3 Basic plot with matplotlib

    Lecture2.4 Histograms

    Lecture2.5 Customization

    Lecture2.6 Boolean logic and control Flow

    Lecture2.7 Pandas

    Lecture3.1 A quick refresh on basic intermediate maths: Preview

    Lecture3.2 Linear Algebra (Vectors, Matrix, Eigen Values)

    Lecture3.3 Probability and Statistics Preview

    Lecture3.4 Hypothesis testing

    Lecture3.5 Optimization

    Lecture4.1 A quick crash course on basics of Python

    Lecture4.2 What is Python

    Lecture4.3 Working with Python

    Lecture4.4 Basic scripts on

    Lecture4.5 Read, write, data handling

    Lecture4.6 Loops

    Lecture4.7 Conditions (if-else)

    Lecture4.8 Function

    Lecture4.9 Code modularization

    Lecture4.10 Scikit-Learn package

    Lecture4.11 Basic visualization

    Lecture5.1 If Statement

    Lecture5.2 for Statement

    Lecture5.3 The range() Function

    Lecture5.4 break and continue statements and else clauses on loops

    Lecture5.5 pass statements

    Lecture5.6 defining statements

    Lecture5.7 more defining statements

    Lecture5.8 Default Argument Values

    Lecture5.9 Keyword Argument

    Lecture5.10 Arbitary Argument Lists

    Lecture5.11 Unpacking Argument Lists

    Lecture5.12 Lambda Expressions

    Lecture5.13 Documentation Settings

    Lecture5.14 Intermezzo : Coding Style

    Lecture6.1 Lists details

    Lecture6.2 Using Lists as Stacks

    Lecture6.3 Using USN as Queues

    Lecture6.4 Functional Programming Tools

    Lecture6.5 list Comprehensions

    Lecture6.6 Nested List Comprehensions

    Lecture6.7 The del statement

    Lecture6.8 Tupfes and Sequences

    Lecture6.9 Sets

    Lecture6.10 Dictionaries

    Lecture6.11 Looping Techniques

    Lecture6.12 More on Conditions

    Lecture6.13 Comparing Sequences and Other Types

    Lecture6.14 Modules details

    Lecture6.15 Executing modules as scripts

    Lecture6.16 The Module Search Path

    Lecture6.17 Compiled’ Python files

    Lectures6.18 Standard Modules

    Lectures6.19 The dir() Function

    Lectures6.20 Packages

    Lectures6.21 Importing • From a Package

    Lectures6.22 Intra-package References

    Lectures6.23 Packages in Multiple Directories

    Lectures6.24 Input & Output

    Lectures6.25 Errors and Exceptions

    Lecture7.1 Names & Objects

    Lecture7.2 Python Scopes and Namespaces

    Lecture7.3 Classes

    Lectures7.4 Class Definition Syntax

    Lectures7.5 Class Objects

    Lectures7.6 Instance Objects

    Lectures7.7 Method Objects

    Lectures7.8 Class and Instance Variables

    Lectures7.9 Random Remarks

    Lectures7.10 Inheritance

    Lectures7.11 Multiple Inheritance

    Lectures7.12 Private Variables and Class-local References

    Lectures7.13 Odds and Ends

    Lectures7.14 Exceptions Are Classes Too

    Lectures7.15 Iterators

    Lectures7.16 Generators

    Lectures7.17 Generator Expressions

    s

    Lecture8.1 List of Use Cases and Projects

    Lecture9.1 Students would be given challenging real life cases to solve – just to augment their learning skills

    Reviews