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 |
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Module 6: Array types | Module 7: Dictionaries | Module 8: Working with Files | Module 9: Modular Programming with functions | Module 10: Errors and Exception Handling |
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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 |
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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 |
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COURSE TYPE: CLASSROOM
DATE | DAY | QATAR TIME |
7-11 Mar 21 | Sun-Thu | 09:00-15:00 |
11-15 Apr 21 | Sun-Thu | 09:00-15:00 |
9-13 May 21 | Sun-Thu | 09:00-15:00 |
13-17 Jun 21 | Sun-Thu | 09:00-15:00 |
11-15 Jul 21 | Sun-Thu | 09:00-15:00 |
8-12 Aug 21 | Sun-Thu | 09:00-15:00 |
12-16 Sep 21 | Sun-Thu | 09:00-15:00 |
10-14 Oct 21 | Sun-Thu | 09:00-15:00 |
14-18 Nov 21 | Sun-Thu | 09:00-15:00 |
12-16 Dec 21 | Sun-Thu | 09:00-15:00 |
TESTIMONIAL
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Meet THE INSTRUCTORS
Instructor Name
Profession
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Instructor Name
Profession
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