ZERO to GOD Python 3.8 FULL STACK MASTERCLASS 45 AI projects

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ZERO to GOD Python 3.8 FULL STACK MASTERCLASS 45 AI projects provided by Udemy is a comprehensive online course, which lasts for 30 hours worth of material. ZERO to GOD Python 3.8 FULL STACK MASTERCLASS 45 AI projects is taught by Gopal Shangari. Upon completion of the course, you can receive an e-certificate from Udemy. The course is taught in Englishand is Paid Course. Visit the course page at Udemy for detailed price information.

Overview
  • 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.

    This is the definitely the most advanced yet simple Python fullstack courseonline. 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 FULLSTACKPython 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 willteach you HTML, CSS, Bootstrap, Javascript, jQuery andPython 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.