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:

To give fundamental information about Artificial Intelligence  and related technologies

To understand how AI is used in Information Technologies

With several sample programs and projects, prepare you to Industry 4.0

Learn Artificial Intelligence using Python, R, Google Colab, UIPath, Power BI.

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:

1. Introduction

2. Information Technologies

3. Application Areas: Education, Government, Healthcare, Technology, Commerce, Manufacturing

4. Artificial Intelligence

5. Machine Learning, Robotic Systems, Robotic Vision, Natural Language Processing

6. Best AI Software you need to know

7. Python, R, Google Colab, Anaconda, UIPath, Power BI

8. Practical AI Examples

9. With CakeMix, opening Excel files and draw graphs automatically

10. Make new music in the computer

11. Face and identify recognition from images

12. Extract texts from digital images, read license plates

13. Convert text files to sound files

14. Make digital assistant

15. Mobile App Programming

16. Android, iOS Examples

17. RESTful API Programming

18. AI Python Package Programming

19. 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, Contd

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

Dr. Mesut Varl?o?lu
Technology Consultant/Yeni ürün Geli?tirme Uzman?

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

Frequently Asked Questions

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