Artificial Intelligence

Artificial intelligence (AI) is wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence.

Instructor: Muheeb Abid
Last updated Sun, 19-Jun-2022
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Course overview

Course Description

Artificial intelligence (AI) is wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence.... It is the endeavor to replicate or simulate human intelligence in machines.

AI includes machine learning as well as deep learning. ... On one hand, machine learning algorithms are helping businesses evolve, and on the other, speech recognition, image processing techniques and fingerprint patterns are taking the world by storm. We use gadgets that are intelligent and makes our everyday tasks easy.

Certificate

On successful completion of the course participants will be awarded participation certificate from DigiPAKISTAN. Also prepare for International Exam.

Duration & Frequency

Total Duration of the course is 6 months

What will i learn?

  • On successful completion of the course participants will be awarded participation certificate from DigiPAKISTAN. Also prepare for International Exam.
Requirements
  • Minimum Matric can join
Curriculum for this course
Introduction
  • Introduction and Course Overview
Programming Fundamentals
  • Intructor Profile
  • Motivation
  • What is AI
  • AI Narrow and General Intelligence
  • Turing Test
  • AI Phenomena
  • AI Gold Rush
  • AI Gold Rush2
  • Course Outline
  • What is program
  • Programming paradigms
  • Compiler Vs Interpreter
  • Seeting up environment
  • Overivew of jupyter notebook
  • Keywords in python
  • print statement
  • variables
  • Operators
  • Expressions
  • Eliminating ambiguity
  • String concatentation
  • structured programming
  • if statements
  • Comparison operators
  • Check greater of two number
  • and operator
  • or operator
  • Nested If .else
  • Concatenation
  • Comments
  • introduction to List
  • Slicing in a list
  • Slicing with negative indices
  • Deleting an element from list
  • Tuple
  • For loop
  • Search in a loop
  • Some functions
  • Dictionary
  • Introduction to functions
  • Functions with positional arguments
  • Keyword arguments
  • Default arguments
  • Unknown number of arguments with tuples
  • Unknown number of arguments with dictionaries
  • Local Vs global variables
  • Call back functions
  • While loops
  • Classes
  • Object Oriented Analysis and Design
  • Pillars of OOP
  • Encapsulation
  • Inheritance
  • Method Overriding
  • Polymorphism
  • Modules
  • I/O
  • Exception Handling
  • Random module
  • Math and sys module
  • docstring
  • String formatting
  • Strings
  • DateTime module
Data Science
  • Module overview
  • Introduction to numpy
  • Vectorized operations
  • Installing numpy
  • Arrays Vs List
  • Which is faster, an experiment
  • Lazy evaluation
  • Magic commands of jupyter
  • List comprehension
  • Mulitplying list in python
  • Multiplying arrays in numpy
  • ndarray
  • Examples of array creation
  • Demonstration of array creation methods
  • Summary of array creation methods
  • shape, ndim, dtype attributes
  • Shape example
  • Data types in numpy
  • Vectorization, indexing and slicing
  • Element-wise array functions
  • np.where()
  • transpose, mean, cumsum, cumprod
  • Boolean funnctions
  • sorting, unique and filing operations
  • Linear algebra operatoins
  • Random number generation
  • reshape and flatten
  • concatenate, hstack, vstack, np.r_ and np.c_
  • ravel Vs flatten
  • Drawing patterns using numpy
  • Introduction to pandas
  • Series
  • DataFrame
  • loc/iloc
  • Adding, removing, updating values
  • Apply function
  • Some useful functions
  • Reading and writing to files
  • Dropping rows from data frame
  • Dropping columns
  • Reading data from files
  • Database - creating tables and inserting data
  • Retrieving data from database
  • Data preprocessing and cleaning
  • Dropna
  • Dropna with threshold
  • Fillna
  • Removing duplicates
  • Map
  • Discretization and binning
  • Describing and finding outliers
  • Merge two frames
  • Join two frames
  • Concatenate frames
  • Introduction to matplotlib
  • Customizing plots
  • Specifying colors
  • Specifying limits
  • Scatter plots
  • Bargraph
  • Histograms
  • Box plots
  • Pie chart
  • Heatmaps
Machine Learning
  • Machine Learning
  • Components of machine learning
  • Tasks of machine learning
  • Various types of tasks
  • Introduction to sk-learn
  • Training and testing
  • Building a mdodel in scikit-learn
  • Performance measures
  • Precision Recall
  • Overfitting and underfitting
  • Machine Learning classifiers - 1
  • Machine LEarnign classifiers - 2
  • sk-learn examples
Semantic Web
  • Semantic Web
  • Ontology
  • Requirements for good ontology language
  • RDF
  • RDF(S)
  • OWL
  • OWL Example
  • Protege
  • Creating classes
  • Creating data type properties
  • Creating object properties
  • Creating individuals
  • Visualization
  • SPARQL
  • Introduction to JENA
  • Setting up JENA
  • Introduction to Java
  • Creating RDF Resources and Statements
  • Alternate way of creating resources
  • Listing RDF statements
  • Getting details from model
  • Simple Selector
  • OWL
  • OWL Reasoning SPARQL Query
NLP
  • Introduction
  • One-hot encoding
  • One-hot encoding impelementation
  • Bag of words
  • Bag of words impelementation
  • Distance between two sentences
  • Case normalization
  • Stop words removal
  • Stemming and lemmatization
  • Regular expressions and chatbot
Data Visualization
  • Introduction
  • Loading data
  • Transformation
  • Bar Chart
  • Multiple graphs
  • Sheets and focus
  • Filtering
  • Edit Interactions
  • Format options
  • Analytics
  • Analytics
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About instructor

Muheeb Abid

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Includes:
  • Verified Certificate
  • Internship Opportunity
  • Career Development