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Linear Algebra For Data Science Machine Learning In Python

Course

LINEAR ALGEBRA FOR DATA SCIENCE MACHINE LEARNING IN PYTHON

Category

Python and Data Science Online Training

Eligibility

Technology Learners

Mode

Both Classroom and Online Classes

Batches

Week Days and Week Ends

Duration :

Fast Track and Regular 60 Days

Python and Data Science What will you learn?

•Learn the core concepts of Python and Data Science.
•Learn to manage application state with Python and Data Science.
•A Beginner’s Guide to Python and Data Science Coding from scratch
•Learn how to structure a large-scale project using Python and Data Science.
•Understand when and how to use Python and Data Science elements variables.
•Learn Python and Data Scienceat a minimal cost and enjoy the instructor support.
•Get straight to the point! Learn the basics of Python and Data Science
•you will be confident in your skills as a Developer / designer
•Have an understand of Python and Data Science and how to apply it in your own programs

linear algebra for data science machine learning in python Course Features

•You Get Real Time Project to practice
•Course has been framed by Industry experts
•Highly competent and skilled IT instructors
•Immersive hands-on training on Python Programming
•Assignments and test to ensure concept absorption.
•Training by Proficient Trainers with more than a decade of experience
•We also provide Normal Track, Fast Track and Weekend Batches also for Working Professionals
•Very in depth course material with Real Time Scenarios for each topic with its Solutions for Online Trainings.

Who are eligible for Python and Data Science

•CNC Engineer, Software Developer, Testing Engineer, Implementation, Core Java, Struts, hibernate, Asp.net, c#, SQL Server, CNC Programming, backDBA, Developers, Programmers, Software Engineers, QA Managers, Product Managers, Development Managers, Mobile Developers, IOS Developers, Android
•Java tech lead,Java Programming, Java / J2Ee Spring, Java Server Pages, Android, IOS Developer, hibernate, Spring, Core Java
•Qa, Ui/ux, Java Developer, Java Architect, C++/qt, Php, Lamp, Api, J2ee, Java, Soa, Esb, Middleware, Bigdata Achitect, Hadoop Architect, Deep
•Solution Architect, Technical Lead, Software Developer, Testing Engineer, Project Manager, sap, sas, sql, magento, wordpress, laravel, mysql, Payment Gateways

LINEAR ALGEBRA FOR DATA SCIENCE MACHINE LEARNING IN PYTHON Syllabus

Welcome to Course!
•Python Basics and Data Types
•Installation and Setup
•Basics
•Variables
•Data Types Introduction
•Numbers
•Strings Part 1
•Strings Part 2
•Strings Part 3
•Strings Part 4
•Lists
•Dictionaries
•Tuples
•Sets
•Booleans
•Statements, Functions and OOP in Python
•If, Elif and Else
•For loop
•While Loop
•Useful functions in Python
•Functions Part 1
•Functions Part 2
•Map, Filter and Lambda Expression
•Scope of Variables in Python
•Introduction of Object Oriented Programming
•Class and Attributes
•Methods
•Inheritance
•Data Analysis with NumPy and Pandas
•Introduction to NumPy
•NumPy Arrays
•NumPy Arrays : Indexing and Selection
•NumPy Operations
•Introduction of Pandas
•Pandas Series
•DataFrames Part 1
•DataFrames Part 2
•DataFrames Part 3
•Working with Missing Data
•Groupby Method
•Merging, Joining and Concatenating DataFrames
•Pandas Operations
•Reading and Writing Files
•Linear Algebra And Python
•Lecture 1 – Linear System of Equations
•Lecture 2 – Elimination Method
•Lecture 3 – Gaussian Elimination Part 1
•Lecture 4 – Gaussian Elimination Part 2
•Lecture 5 – Gaussian Elimination Part 3
•Lecture 6 – Applications of Gaussian Elimination
•Lecture 7 – Row Echelon Form
•Lecture 8 – Row Echelon Form 2
•Lecture 9 – Matrix Algebra 1
•Lecture 10 – Matrix Algebra 2
•Python 1 – Matrix Algebra in Numpy
•Lecture 11 – Special Matrices, Diagonal and Inverse Matrices
•Lecture 12 – Special Matrices, Diagonal and Inverse Matrices Part 2
•Lecture 13- Inverse Matrices Continued
•Lecture 14 – Inverses and Transpose
•Lecture 15 – Determinants
•Lecture 16 – Determinants 2
•Python 2 – Inverse, Determinant Calculat
•Lecture 17 – Computation of Determinants
•Lecture 18 – Linear Regression in Python