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.