Quick-Start for Managers;Artificial Intelligence ( AI )
Introduction to Data Science, Machine Learning, Deep Learning & Neural Networks for Beginners with Scikit-Learn & Python
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.
Technology Explained in Simple Terms
The only background you need is 10th grade high-school Math.
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 experiencedeveloping machine learning systems for industry projects. Everything is explained in such simple terms that you need only 10th grade high school math to understand it.
Enroll today & accelerate your career with AI.
Your Instructor
Hi! We are UpDegree, providing high quality interactive course.
We are the team of 100+ instructor over the globe. Adel (Oxford), Anand (Standford), Akash (IITB), Rajib (IITK), Partha (IITM) are few of them.
Updegree courses are different, In each and every course you not only get the videos lectures but you also get quiz,code,assignment etc to test your practical understanding!
Course Curriculum
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StartIntroduction and Outline (7:22)
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StartSpeed Up the Learning Process (4:33)
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StartPreventing Underfit & Overfit (7:29)
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StartClassification (8:24)
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StartSigmoid Models for Classification (5:56)
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StartRegularization - Part 1Regularization - Part 1 (5:59)
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StartRegularization - Part 2 (3:28)
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StartMachine Learning Libraries (7:52)
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StartCoding with Python & Scikit Learn (1:33)
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StartMulti-Layer Neural Networks & Deep Learning - Part 1 (4:45)
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StartMulti-Layer Neural Networks & Deep Learning - Part 2 (11:57)
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StartConvolutional Neural Network - Part 1 (4:28)
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StartConvolutional Neural Network - Part 2 (4:05)
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StartRecurrent Neural Networks (4:22)
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StartStart From Published Papers (14:49)
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StartMachine Learning or Deep Learning? (3:42)
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StartBuild or Buy? (1:40)
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StartRe-use Models and Libraries (3:00)
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StartWord Embeddings (9:02)
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StartUsing Embeddings for Natural Language Processing (7:51)
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StartTraining with Artificial Data (19:09)