Practical Artificial Intelligence
Practical Artificial Intelligence, available at $59.99, has an average rating of 4.4, with 77 lectures, based on 23 reviews, and has 1208 subscribers.
You will learn about Learn about Artificial Intelligence and related technologies with practical examples and information. Be familiar with Python, R, UIPath, Power BI and mobile app programming Create new applications using Machine Learning, Deep Learning, and Computer Vision Learn about Data Science and Exploratory Data Science tools Create forecasting analysis using AI tools and predict future orders Develop object detection, face recognition, voice cloning tools using Artificial Inteligence Automatically make standalone web documents and presentations using Python Bokeh This course is ideal for individuals who are Anyone who wants to learn Python, R, UIPath, Power BI, and mobile app programming or Beginner Python developers who are interested in Artificial Intelligence and Data Science It is particularly useful for Anyone who wants to learn Python, R, UIPath, Power BI, and mobile app programming or Beginner Python developers who are interested in Artificial Intelligence and Data Science.
Enroll now: Practical Artificial Intelligence
Summary
Title: Practical Artificial Intelligence
Price: $59.99
Average Rating: 4.4
Number of Lectures: 77
Number of Published Lectures: 77
Number of Curriculum Items: 77
Number of Published Curriculum Objects: 77
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn about Artificial Intelligence and related technologies with practical examples and information.
- Be familiar with Python, R, UIPath, Power BI and mobile app programming
- Create new applications using Machine Learning, Deep Learning, and Computer Vision
- Learn about Data Science and Exploratory Data Science tools
- Create forecasting analysis using AI tools and predict future orders
- Develop object detection, face recognition, voice cloning tools using Artificial Inteligence
- Automatically make standalone web documents and presentations using Python Bokeh
Who Should Attend
- Anyone who wants to learn Python, R, UIPath, Power BI, and mobile app programming
- Beginner Python developers who are interested in Artificial Intelligence and Data Science
Target Audiences
- Anyone who wants to learn Python, R, UIPath, Power BI, and mobile app programming
- Beginner Python developers who are interested in Artificial Intelligence and Data Science
In Practical Artificial Intelligence course, artificial intelligence technologies and their usage areas will be explained with examples. Purpose of education:
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To give fundamental information about Artificial Intelligence and related technologies
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To understand how AI is used in Information Technologies
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With several sample programs and projects, prepare you to Industry 4.0
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Learn Artificial Intelligence using Python, R, Google Colab, UIPath, Power BI.
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Introducing a new distance education, combined with knowledge and experience.
Target Participants:Newly graduated university students, high school students, administrators, entrepreneurs, anyone who wants to improve themselves.
Here are the contents of the Practical Artificial Intelligence course:
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Introduction
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Information Technologies
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Application Areas: Education, Government, Healthcare, Technology, Commerce, Manufacturing
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Artificial Intelligence
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Machine Learning, Robotic Systems, Robotic Vision, Natural Language Processing
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Best AI Software you need to know
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Python, R, Google Colab, Anaconda, UIPath, Power BI
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Practical AI Examples
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With CakeMix, opening Excel files and draw graphs automatically
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Make new music in the computer
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Face and identify recognition from images
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Extract texts from digital images, read license plates
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Convert text files to sound files
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Make digital assistant
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Mobile App Programming
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Android, iOS Examples
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RESTful API Programming
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AI Python Package Programming
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Next steps
We are looking forward to be working with you to create best AI tools for your needs.
When you complete this course, you will receive a certificate from Udemy and we will provide you all source codes for the courses.
Course Curriculum
Chapter 1: Preview and Contents
Lecture 1: Preview
Lecture 2: Contents
Lecture 3: Practical AI Course Guide
Chapter 2: Introduction
Lecture 1: Introduction
Chapter 3: Information Technologies
Lecture 1: Information Technologies
Chapter 4: Artificial Intelligence
Lecture 1: Artificial Intelligence
Lecture 2: Artificial Intelligence Current Applications
Lecture 3: Natural Language Processing – Part 1 (Optional)
Lecture 4: Natural Language Processing – Part 2 (Optional)
Lecture 5: Natural Language Processing – Part 3 (Optional)
Lecture 6: Natural Language Processing – Part 4 (Optional)
Chapter 5: AI Software and Programming
Lecture 1: List of AI Software
Lecture 2: Anaconda Python Installation
Lecture 3: Anaconda Python using Spyder
Lecture 4: Anaconda Python using Spyder – Variables, Lists, Loop, If Statements
Lecture 5: Python Installing and Running Packages
Lecture 6: Anaconda Jupyter Notebook, How to use
Lecture 7: Anaconda Jupyter Notebook, Cont'd
Lecture 8: Google Colab, Free Python Development Environment
Lecture 9: R vs Python
Lecture 10: UIPath Introduction
Lecture 11: UIPath Example – Opening Excel Files, Displaying Data
Lecture 12: Power BI Introduction
Lecture 13: Power BI Example – Installing and Getting Data
Lecture 14: Power BI Example – Plotting Data, Filters
Lecture 15: Power BI Example – Customizing, Publishing Dashboard
Chapter 6: AI Examples – Overview – Simple
Lecture 1: AI Examples Overview and Frequently Asked Questions
Lecture 2: Python Training, Functions, Classes
Lecture 3: Excel Automation with Cakemix
Lecture 4: Music Automation Part 1
Lecture 5: Music Automation Part 2
Lecture 6: Music Automation Part 3
Lecture 7: Music Automation Final
Lecture 8: Face Recognition from Digital Images
Lecture 9: Face Recognition from Digital Images Final
Lecture 10: Reading Text Files and License Plates from Digital Images
Lecture 11: Converting Text to Speech Files
Lecture 12: Digital Assistant – Pet Care
Lecture 13: Digital Assistant – Pet Care Final
Chapter 7: AI Examples – Data Science
Lecture 1: Data Science related AI topics
Lecture 2: NLP Spam Classifier
Lecture 3: NLP Spam Classifier – Part 2
Lecture 4: NLP Spam Classifier – Part 3
Lecture 5: NLP Spam Classifier – Part 4
Lecture 6: NLP Spam Classifier – Part 5
Lecture 7: NLP Spam Classifier – Part 6
Lecture 8: NLP Spam Classifer – Part 7
Chapter 8: Mobile Application and AI
Lecture 1: Mobile Communication and App Background
Lecture 2: Mobile App Examples – Background
Lecture 3: Mobile App Example – Creating Ionic App
Lecture 4: Source Code of the App we will create
Lecture 5: Mobile App Example – Creating Pages, Routing, Tab Menu
Lecture 6: Mobile App Example – Grids, Rows, Columns, Styling
Lecture 7: Mobile App Example – Ion Cards, Course Page
Lecture 8: Mobile App Example – External Images, Text Styling, About Page Complete
Lecture 9: Restful API and Mobile App AI, Introduction
Lecture 10: Installing Xampp, PHP_MySql Server
Lecture 11: PHP MySQL Introduction
Lecture 12: Creating MySQL Database and Table
Lecture 13: Making REST Api in PHP and MySQL
Lecture 14: Reading REST API data in the Mobile App
Lecture 15: Reading MySQL Database with Python
Lecture 16: Reading Data from Excel and Inserting Database with Python, Completing AI App
Chapter 9: How to Create and Publish Python Package
Lecture 1: Write and Publish Python Packages
Chapter 10: Next Steps
Lecture 1: Next Steps for AI
Chapter 11: Bonus Content: Practical Artificial Intelligence Projects
Lecture 1: AI Projects Overview
Lecture 2: Pandas Overview
Lecture 3: Exploratory Data Science using Pandas
Lecture 4: Pandas Profiling to automate Exploratory Data Science analysis
Lecture 5: Sweetviz as Exploratory Data Science Automation
Lecture 6: One Hot Encoder to Convert NonNumeric Data to Numeric Values
Lecture 7: Forecasting Future Orders using FB Prophet
Lecture 8: Object Detection from digital images using TensorFlow
Lecture 9: Real Time Voice Cloning using TensorFlow
Lecture 10: Creating Interactive Graphs, Tables, Sliders with Python Bokeh
Lecture 11: Screen Annotation Tools using Python ScreenPen
Lecture 12: How to Create 8D Music using AI
Instructors
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Dr. Mesut Varlıoğlu
Technology Consultant/Yeni Ürün Geliştirme Uzmanı -
Dr. Tolga Akiner
Data Scentist
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 0 votes
- 3 stars: 2 votes
- 4 stars: 10 votes
- 5 stars: 11 votes
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