Courses Details

Course Type : paid
Duration : 120 hrs
Category
AI and Data Science
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Course Description

<p>Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include&nbsp;expert systems, natural language processing, speech recognition and&nbsp;machine vision.</p>

Curriculum

    • Introduction to Programming
    • Introduction to Python and How Python Works
    • Introduction to Python Basic Course Structure
    • How to install Python
    • How to run Python Program using Command Line Window, IDLE, Notepad
    • How to install Anaconda and run jupyter notebook for python
    • Comments, Identifier, Reserved Words and Constant in Python
    • Variable in Python
    • Data Type in Python
    • Declaring and Intializing Variables in Python
    • Operators in Python
    • Implicit and Explicit Type Conversion in Python
    • Output Statement or Print Function in Python
    • Getting input from user or Input Statement or input Function in Python
    • Escape Sequence in Python
    • If Statement in Python
    • Nested if Statement in Python
    • if Statement with Logical Operator in Python
    • Indentation in Python
    • if else Statement in Python
    • Nested if else Statement in Python
    • if elif and if elif else Statement in Python
    • range Function in Python
    • For Loop and Nested for Loop in Python
    • Enumerate() in Python with EXAMPLES
    • While Loop and Nested while Loop in Python
    • Break, Continue and Pass Statement in Python
    • String in Python
    • More on Strings(Access string using loop, repetitation and concatenation in string, mutable and immutable)
    • String Formatting in Python
    • String Methods in Python
    • List in Python
    • List methods in python
    • More on Lists (Use loops with list, slicing in list, concatenation, repeatition, aliasing, copying and cloning in list)
    • Nested List in Python
    • Tuple and tuple methods in Python
    • More on Tuple(Use loops with tuple, slicing tuple, concatenation, repeatition, aliasing, copying tuple, getting user input as tuple, modifying and deleting tuple)
    • Nested Tuple in Python
    • Set Type in Python
    • Set methods in Python
    • Nested Set in Python - FrozenSet
    • Dictionary in Python
    • Dictionary methods in Python
    • More on Dictionary (Loop in Dictionary, Getting Dictionary input from user)
    • Nested Dictionary in Python
    • Function and How Function Work in Python
    • Arguments and its types in Python
    • Local and Global Variable in Python
    • global Keyword and function in Python
    • Passing and returning List, Tuple, Set, Dictionary in Function
    • Recursion in Python
    • Anonymous Function or Lambda Expression in Python
    • Function Decorator in Python
    • Ternary if
    • List, Tuple, Set and Dictionary Comprehension in Python
    • Nested Comprehension in Python
    • Generator Function Yield Statement and Next Function in Python
    • Type and isinstance Function in Python
    • Len,min,max and sorted Function
    • Zip method
    • Filter, map Function in Python
    • Tips and Tricks in Python
    • Getting Help in Python
    • Class and Object in Python
    • Constructor in Python
    • Inheritance in Python
    • Constructor in Inheritance
    • Method Overloading, Overriding and Method with super in Python
    • Special (Magic/Dunder) Methods
    • Exception Handling and Builtin Exception in Python
    • User Defined Exception in Python
    • Difference between Error and Exception and Warning in Python
    • Installing VSCode and coding in VSCode
    • Debugging in VSCode
    • Introduction to Virtual Environments
    • Using conda and virtual environments with VSCode
    • Module in Python, Math module in python
    • Datetime Class in Python
    • Random, sleep in Python
    • Functools(Reduce and Memoization), getpass(getpass and getuser) and sys Module
    • if __name__ == "__main__"
    • What is File and File Handling in Python
    • Reading Files in Python
    • Write Create Files in Python
    • What is git/ What is Version control system?
    • What is Github?
    • How To Insatll Git
    • Basic Commands: add, commit, push
    • Undoing/Reverting/Resetting code changes
    • Branches (Create, Merge, Delete)
    • What is HEAD?
    • .gitignore file
    • Diff and Merge using vscode
    • What is Pull Request?
    • Brief intro to working with git, github with help of vscode and github desktop
    • Introduction to Libraries
    • Introduction to Web Scrapping - Beautiful Soup
    • Project 1 - Web scraping table from wikipedia
    • PyQt Tutorial: Python GUI Designer
    • Project 2 - Making a simple calculator
    • Image Manipulation with Pillow
    • Project 3 - Adding logo into Multiple images at once.
    • Data on the Web
    • eXtensible Markup Language(XML)
    • XML Schema
    • Parsing XML
    • JSON Introduction
    • Encoding JSON Python Objects
    • Decoding JSON Python Objects
    • Connecting to a server
    • A simple server-client program
    • What is Database?
    • Connect to Database in Python
    • Create a Table
    • Insert Record into Table
    • Query and Fetchall
    • Use the Where Clause
    • Introduction to Machine Learning
    • Key ML Terminology
    • Linear Regression
    • Training  and Loss
    • An alternative Approach
    • Gradient Descent
    • Learning Rate
    • Optimizing Learning Rate
    • Stochastic Gradient Descent
    • Peril of Overfitting
    • Another Partition
    • Feature Engineering
    • Qualities of good feature
    • Cleaning Data
    • Encoding Nonlinearity
    • Crossing One Hot Vectors
    • L2 Regularization
    • Lambda
    • L2 Regularization Exercise
    • Calculating a Probability
    • Loss and Regularization
    • Thresholding
    • True vs False, Positive vs Negative
    • Accuracy
    • Precision and Recall
    • ROC Curve and AOC
    • Prediction Bias
    • L1 Regularization
    • One vs All
    • Softmax
    • Motivation from collaborative filtering
    • Categorical Input Data
    • Translating to a Lower Dimensional Space
    • Obtaining Embeddings
    • Production ML S
    • Static vs Dynamic Training
    • Static vs Dynamic Interface
    • Data Dependencies
    • Fairness
      • Types of Bias
      • Identifying Bias
      • Evaluating for Bias
    • Cancer Prediction
    • Introduction to Google co-lab and Anaconda
    • Numpy
    • Pandas
    • Plotting and Charting
    • Project1: Mini Project
    • Tensorflow
    • Pytorch
    • Keras
    • Theano
    • Computer Vision Overview
    • Image Formation
    • History
    • Introduction to Open CV
    • Different Types of Filter
    • Feature Detection
    • Edge Detection
    • Haar-like Features
    • Frequency Domain Analysis
    • Project2: Face Detection
    • Introduction to Deep Learning
    • History
    • Why Deep Learning Taking Off
    • Building Block of deep Learning
    • Application of Deep Learning
    • Multilayer Perceptron
    • Back Propagation
    • Working Of neural network
    • Adjusting the weights
    • Gradient Descent
    • Stochastic Gradient Descent
    • Foundations of Convolutional Neural Network
    • CNN Architecture
    • Convolution Operation
    • ReLU Layer
    • Pooling
    • Flattening
    • Full Connection
    • Softmax & Cross-Entropy
    • Summary
    • Get the dataset
    • Importing the Libraries
    • Importing the Dataset
    • Splitting the Dataset into the Training set and Test set
    • Feature Engineering
    • Traditional Computer Vision
    • Image classification using Deep Learning
    • Binary and Multi class Image classification
    • Deep learning in Object Detection  SSD,YOLO
    • Project3: Binary and Multi Image Classification
    • Project4: Object Recognition
    • The Idea Behind GANs
      • How Do GANs Work?
    • Generator
    • Discriminator
    • Generative Adversarial Networks Representation
    • Mathematical Details About GANs
      • Applications of GANs
    • Current Research On GAN
    • Project 5: Image Creation with GAN

Instructor

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