Updated for 2020! HTML To Artificial Intelligence Deep Learning Bootcamp Cornell University course w/Machine Learning!
What you'll learn:
Students will be able to create websites, build applications, create Artificial Intelligent learning programs that can recognize handwriting and learn while analyzing data.
Will help you get a job as a Fullstack programmer or Artificial Intelligence data scientist.
Build over 10 AI data analysis tools
My name is GP. IusedAI to classify brain tumors. Ihave 11 publications on Pubmed. Iwent to Cornell and taught at UCSF, NIH, Cornell University and Amherst College.
We are offering LIVEHELPM-F 9-5 and also outside those hours whenonline.
This course will be continually updated and we answer all questions. We will continue updating content based on both user demand and changes in machinelearning and AI. If you have taken a previous bootcamp but still are struggling, this course will fill in the holes and have you applying Python on lots of different projects. You will learn faster by
This is the only fullstack course that teaches you everything from basic frontendHTML to Python 3,Machine learning,Tensor Flow, and Artificial Intelligence /Recurrent Neural Networks!
This is a large course, but it is still easy!The secret to this course is that to learn rapidly, we present information insmall steps, so that no one step seems difficult.Of course,there are lots of steps, so the knowledge builds fast, but itson a very strong foundation.
With over 170 lectures and more than 30 hours of video this course is extremely comprehensive
We cover a wide variety of topics, including:
Bootstrap (to make responsive websites fast!)
jQuery (to further interact with users using clicks and mouseovers)
Running Python Code
Object Oriented Programming
Number Data Types
Debugging and Error Handling
Decorators/ Advanced Decorators
and much more!
For Data Science / Machine Learning / Artificial Intelligence
1. Machine Learning
2. Training Algorithm
4. Data Preprocessing
5. Dimesionality Reduction
6. Hyperparemeter Optimization
7. Ensemble Learning
8. Sentiment Analysis
9. Regression Analysis
11. Artificial Neural Networks
13. TensorFlow Workshop
14. Convolutional Neural Networks
15. Recurrent Neural Networks
Traditional statistics and Machine Learning
1. Descriptive Statistics
2.Classical Inference Proportions
3. Classical InferenceMeans
4. Bayesian Analysis
5. Bayesian Inference Proportions
6. Bayesian Inference Means
12. Decision Tree
13. Random Forests
15. Evaluating Linear Model
16. Ridge Regression
17. LASSO Regression
19. Perceptron Basic
20. Training Neural Network
21. Regression Neural Network
23. Evaluating Cluster Model
25. Hierarchal 26. Spectral
29. Low Dimensional
You will get lifetime access to over 180 lectures plus corresponding Notebooks for the lectures!
This course comes with a 30 day money back guarantee! If you are not satisfied in any way, you'll get your money back.
Learn Python and AI in the easiest possible way, so you can advance your career quickly and easily.
Who is the target audience?
Beginners who have never programmed before.
People who took a programming bootcamp but are looking to apply that knowledge to build something other than very basic projects.
Intermediate Python programmers who want to understand Artificial Intelligence Programming.