Introduction to Artificial Intelligence ( AI ) for Managers
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 44100 Hz, 2ch | Size: 873 MB
Genre: eLearning Video | Duration: 26 lectures (1 hours, 47 mins) | Language: English
Data Science, Machine Learning, Deep Learning & Neural Networks for Beginners with Scikit-Learn & Python
Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 44100 Hz, 2ch | Size: 873 MB
Genre: eLearning Video | Duration: 26 lectures (1 hours, 47 mins) | Language: English
Data Science, Machine Learning, Deep Learning & Neural Networks for Beginners with Scikit-Learn & Python
What you'll learn
Understand how AI works at a technical level. Manage machine learning and deep learning projects.
Use AI libraries like Scikit-Learn
Understand how Multi-layer Neural Networks learn features automatically
Learn about deep learning algorithms like convolutional neural networks
Requirements
Basic School Math at 10th grade level
Basic knowledge of Algorithms.
Be able to understand a technical description of an algorithm.
Description
Do you want to learn Artificial Intelligence technology quickly?
Are you a manager, director, or VP who needs to understand how AI works at a technical level?
This fast-paced course explains the core concepts of Artificial Intelligence through engaging animations. In less than 2 hours you will be able to:
- Identify opportunities for using AI in your business
- Evaluate technical solutions
- Manage AI development projects
- Estimate resource requirements for your AI project
- Reuse pre-trained libraries to save cost
… and lead your AI project to success.
Prerequisites
You must be adept with 10th grade level high-school Math.
This course describes AI algorithms at a technical level. You need to be able to understand step-by-step descriptions of algorithms.
Though this is a non-coding introduction, some knowledge of programming will make it easier to understand the algorithms presented.
Technology Explained in Simple Terms
You will be able to apply these algorithms in your own projects: kNN, Stochastic Gradient Descent, Regularization, Support Vector Machines, Random Forests, Classification with Sigmoids, Multi-Layer Neural Nets, Deep Learning with Convolutional Neural Networks and Recurrent Nets, and Natural Language Processing with Word-Embeddings.
Real-world project:
You will build an AI system that detects cancer. The code is explained clearly line-by-line. No prior programming knowledge is required. This project is developed on Python with the Scikit-Learn library.
Experience:
The material in this course is built upon 15 years of my experience developing machine learning systems for industry projects.
Enroll today & accelerate your career with AI.
Who this course is for:
AI Managers, Project Leaders, Directors, Vice-Presidents who have worked in technology, and need to learn AI quickly