INTRODUCTORY COURSE

Deep learning series is the intensive hands-on course leading to the capacity of creating and managing strong AI systems.

During my courses I realized the difficulties for students who begin their journey into this new universe. So many elements, techniques, softwares, different logical approaches, most students get lost or take very difficult paths. I created this introductory course with the purpose to help you having the best and clearest approach to Deep Learning and accelerating your learning to the maximum.

In this course you will have for 7 consecutive days 4 hours/day lesson + 4 hours/day hands on programming a supercomputer, I and my assistants will drive you, clarify your doubts, explain difficult theories.

Who is this course for: curious people, students, researchers, scientists, programmers. This course is for people loving science and wanting to go deeper.

Prerequisites: curiosity, maths, some programming. The more, the better. Classes will be formed after selection for homogeneus learning.

Cost for online course: 250 US $. Discounts apply UNTIL JANUARY 9. Discounts apply automatically if you have attended other courses with us. You will be asked to pay only if your request of enrollment is accepted; should I think that the class is not suitable to you, I will suggest other courses for creating the basis correctly.

Cost for in-person in-class San Francisco course: 1500 US $. Discounts apply if you have been invited or if you have attended other courses with us. You will be asked to pay if your request of enrollment is accepted.

Date: Course will be taught 1st to 7th every month (January 2nd to 8th). If you take online class you have 30 days to complete assignments and to verify with us.

What happens after the course? You can enter our tutorage programs or you can take internships and/or further courses with us and in these cases our tutorage is free. We want to change the world doing our best and helping everyone to do his/her best.

Doubts? Write to info@strongartificialintelligence.com , subject INTRO2017

Day 1:

Supercomputers and Mathematics: MATLAB/OCTAVE accelerated parallel GPU programming for Machine Learning. Change your vision: algorithms.

Laboratory: Write and test your Matlab / Octave algorithm

Day 2:

Enlarge your vision with R for big data sets. Manage Matlab/Octave routines through Python. Build a powerful agent.

Laboratory: write and test R and Python agents for your algorithm

Day 3:

C++: the glue of your code. Get access to powerful C++ libraries.

Laboratory: Create and use C++ libraries for feeding your agents

Day 4:

CUDA day, go deep parallel programming. Top technology of nVidia.

Laboratory: write CUDA code for having your algorithm broken in thousands of threads and keep them optimized and under control. Execution time must be not longer than 10% of not optimized code if you have a recent nVidia GPGPU.

Day 5:

TensorFlow. Machine Learning. How to program it. Top technology of Google. Deep Neural Networks. Convolutional Neural Networks.

Laboratory: Have TensorFlow working your data. Implement it. Execution time must be not longer than 10% of optimized code from yesterday and not longer than 1% of not optimized code, if you have a recent nVidia GPGPU.

Day 6:

Training day. Design and implement Deep Neural Networks for training purpose for your algorithm.

Laboratory: Improve your code. Execution time must be not longer than 10% of optimized code for TensorFlow from yesterday and not longer than 1% of optimized code and not longer than 0.1% of not optimized code, if you have a recent nVidia GPGPU.

Day 7:

Your algorithm is now AI. Feed it with Big Data. Search and use hyperparameters. Classify.

Laboratory: One billion data set. Adapt and correct your code. Train your DNNs. Try to make your new born Strong Artificial Intelligence.

When: every month 1st to 7th (only on January 2nd to 8th). Course is 8 hours/day,  morning lessons class 9 am to 1 pm and afternoon laboratory class 1.30 pm to 5.30 pm

Where: company HQ, 101 California Street Suite 2710, San Francisco CA 94111 

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