Udemy course ZERO to GOD Python 3.8 FULL STACK MASTERCLASS 45 AI projects by Gopal Shangari
ZERO to GOD Python 3.8 FULL STACK MASTERCLASS 45 AI projects is the best Udemy course on the market. With this offer they will be able to greatly improve their knowledge and become more competitive within the Development category. Therefore, if you are looking to improve your Development skills we recommend that you download ZERO to GOD Python 3.8 FULL STACK MASTERCLASS 45 AI projects udemy course.
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Course data:
- Author: Gopal Shangari
- Course rating: 4.4
- Category: Development
- Modality: Online
- Status: Available
- Idiom: English
Abouth Gopal Shangari
BA Degree from Computer Science and Neuroscience from Cornell University in Ithaca NY
What the udemy ZERO to GOD Python 3.8 FULL STACK MASTERCLASS 45 AI projects course teaches?
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
Updated for 2020! HTML To Artificial Intelligence Deep Learning Bootcamp Cornell University course w/Machine Learning!
More information about the course ZERO to GOD Python 3.8 FULL STACK MASTERCLASS 45 AI projects
My name is GP. I used AI to classify brain tumors. I have 11 publications on Pubmed. I went to Cornell and taught at UCSF, NIH, Cornell University and Amherst College. We are offering LIVE HELP M-F 9-5 and also outside those hours when online. This course will be continually updated and we answer all questions. We will continue updating content based on both user demand and changes in machine learning 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 frontend HTML 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 in small steps, so that no one step seems difficult. Of course, there are lots of steps, so the knowledge builds fast, but its on a very strong foundation. This is the definitely the most advanced yet simple Python fullstack course online. There is no other course ANYWHERE that goes as far into Data Science and Machine learning/ Artificial Intelligence as a stand alone topic, let alone with a FULLSTACK Python course preceding the data science. We can literally take someone with no programming experience and have them doing AI programs in about 2 weeks (or faster if they study daily). Whether you have never programmed before, already know basic syntax, or want to finally advance your skillset, this course is for you! In this course we will teach you HTML, CSS, Bootstrap, Javascript, jQuery and Python 3. With over 170 lectures and more than 30 hours of video this course is extremely comprehensive We cover a wide variety of topics, including: HTML CSS Bootstrap (to make responsive websites fast!) Javascript (to interact with users) jQuery (to further interact with users using clicks and mouseovers) Installing Python Running Python Code Strings External Modules Object Oriented Programming Inheritance Polymorphism Lists Dictionaries Tuples Sets Number Data Types Print Formatting Functions Scope args/kwargs Built-in Functions Debugging and Error Handling Modules File I/O Advanced Methods Decorators/ Advanced Decorators and much more! For Data Science / Machine Learning / Artificial Intelligence 1. Machine Learning 2. Training Algorithm 3. SciKit 4. Data Preprocessing 5. Dimesionality Reduction 6. Hyperparemeter Optimization 7. Ensemble Learning 8. Sentiment Analysis 9. Regression Analysis 10.Cluster Analysis 11. Artificial Neural Networks 12. TensorFlow 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 7. Correlations 11. KNN 12. Decision Tree 13. Random Forests 14. OLS 15. Evaluating Linear Model 16. Ridge Regression 17. LASSO Regression 18. Interpolation 19. Perceptron Basic 20. Training Neural Network 21. Regression Neural Network 22. Clustering 23. Evaluating Cluster Model 24. kMeans 25. Hierarchal 26. Spectral 27. PCA 28. SVD 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.
