Introduction to Artificial Intelligence with Python Programming

overview

Artificial intelligence is the intelligence demonstrated by machines, in contrast to the intelligence displayed by humans. This course covers the basic concepts of various fields of artificial intelligence like Artificial Neural Networks, Natural Language Processing, Machine Learning, Deep Learning, Genetic algorithms etc., and its implementation in Python.

Python is a general-purpose programming language that is becoming more and more popular for doing data science and artificial intelligence based applications.
At the beginning of the course, you will learn basic syntax, operators, variables, data types, String, data structures like List, tuples, Dictionaries, Sets, etc.
Later part of the course is Object Oriented Python, Exception handling, File handling and GUI Programming
As part of this course you will get complete hands on experience on IMP data science and AI related Python libraries like NumPy, Pandas, Matplotlib, SciPy, etc.

course details

COURSE DURATION	LANGUAGE	CERTIFICATE
40 Hours – 2 Hours per Day	English	DISS Certificate
	*Please notify us if an interpretation is required

course benefits/progression opportunities

Course objectives

At the end of the training program, participants will learn to:

Understand the importance, principles, and fields of AI
Work with Anaconda and Spider IDE to develop Python applications
Learn core Python scripting elements such as variables and flow control structures, looping statements
Discover how to work with lists and sequence data
Write Python functions to facilitate code reuse
Make code robust by handling errors and exceptions properly
Explore Python’s object-oriented features
Create GUI applications
Work with the most important libraries for doing Data Science with Python and how they can be easily installed with the Anaconda distribution.
Work with Numpy library which is the foundation of all the other analytical tools in Python.
Analyze, answer questions and derive conclusions from real world data sets using the Pandas library.
Produce informative, useful and beautiful visualizations for analyzing data
Perform common statistical calculations and use the results to reach conclusions about the data.

course outline

Module 1: An Overview of Artificial Intelligence	Module 2: Why Python for AI	Module 3: The python environment, Anaconda and Spyder IDE	Module 4: Getting Started with Data types, Operators, Variables	Module 5: Indenting is significant
Basic Concept of Artificial Intelligence (AI) The Necessity of Learning AI Types of Intelligence What’s involved in AI Application of AI Cognitive Modelling: Simulating Human Thinking Procedure Agent & Environment Python for AI Applications	An Overview of Python Interpreted languages Advantages and disadvantages Downloading and installing Which version of Python Where to find documentation	Structure of a Python script Using the interpreter interactively Install Anaconda Start working with Spyder IDE	Using variables String types: normal, raw and Unicode String operators and expressions Math operators and expressions Writing to the screen Command line parameters Reading from the keyboard Flow Control and Loops About flow control	The if and elif statements while loops Using lists Using the for statement The range() function

Module 6: Array types	Module 7: Dictionaries	Module 8: Working with Files	Module 9: Modular Programming with functions	Module 10: Errors and Exception Handling
list operations list methods Strings are special kinds of lists tuples sets	Dictionaries and Sets Dictionary overview Creating dictionaries Dictionary functions Fetching keys or values Testing for existence of elements Deleting elements	Text/csv file I/O overview Opening a text/csv file Reading text /csv files Raw (binary) data Using the pickle module Writing to a text/csv file	Need of modular programming Syntax of function definition Formal parameters Global versus local variables Passing parameters and returning values	Dealing with syntax errors Exception classes Handling exceptions with try/except Cleaning up with finally Raise exceptions

Module 11: Modules and Packages	Module 12: Highlights of the Standard Library	Module 13: Object Oriented Programming with Python	Module 14: GUI Programming with PyQt	Module 15: Database Access
What is a module? The import statement Function aliases Packages	Working with the operating system Grabbing web pages Sending email Using glob for filename wildcards math and random Accessing dates and times with datetime Working with compressed files	About o-o programming Defining classes Constructors Instance methods Instance data Class methods and data Destructors Inheritance, method overloading Data hiding and data encapsulation	Overview Qt Architecture Using designer Standard widgets Event handling	The DB API Available Interfaces Connecting to a server Creating and executing a cursor Fetching data Parameterized statements

Module 16: Data analytics using NumPy	Module 17: Data analytics using Pandas	Module 18: Data visualization using Matplotlib & Pandas visualization	Module 19: Python visualization: Matplotlib and seaborn
NumPy basics Creating arrays Indexing and slicing Large number sets Transforming data Advanced tricks Random number generation	Pandas overview Series and Data frames Reading and writing data Advanced indexing and slicing Merging and joining data sets Analysing Datasets Sorting data Filtering values Basic statistics Leveraging SciPy/NumPy Using pandas Group-by plotting Handling missing data in pandas	Creating a basic plot Commonly used plots Customizing styles Ad hoc data visualization Advanced usage Saving images	Pandas visualization: histograms, bar and box plots Pandas visualization: Scatter plots and pie charts Group-by plotting Pandas plot formatting

COURSE TYPE: WEBINAR
DATE	TIME
11 Oct 2020	11:00 – 13:00 (QATAR)
	12:00 – 14:00 (OMAN)
15 Nov 2020	11:00 – 14:00 (QATAR)
	12:00 – 14:00 (OMAN)
13 Dec 2020	11:00 – 13:00 (QATAR)
	12:00 – 14:00 (OMAN)

TESTIMONIAL

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Meet THE INSTRUCTORS

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Online Self-study Certifications

Introduction to Artificial Intelligence with Python Programming

overview

course details

course benefits/progression opportunities

Course objectives

course outline

TESTIMONIAL

Meet THE INSTRUCTORS

Instructor Name
Profession

Instructor Name
Profession

Related Courses

ITIL Foundation V4

Graphics Design and Video Editing using Adobe Illustrator & Premiere

COBIT Foundation v5

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CONTACT INFORMATION

Introduction to Artificial Intelligence with Python Programming

overview

course details

course benefits/progression opportunities

Course objectives

course outline

TESTIMONIAL

Meet THE INSTRUCTORS

Instructor NameProfession

Instructor NameProfession

Related Courses

ITIL Foundation V4

Graphics Design and Video Editing using Adobe Illustrator & Premiere

COBIT Foundation v5

ITIL Intermediate SO

ITIL Intermediate CSI

HSE COURSES

BUSINESS COURSES

QUICK LINKS

CONTACT INFORMATION

Instructor Name
Profession

Instructor Name
Profession