Complete Machine Learning Course

Simpliv Learning

  • Ratings
  • 4.0
  •  Last updated 3 years ago
  •  ENGLISH

AED 37

AED 185

Duration: 47 to 48 Hours
Location: United Arab Emirates
Delivery: Online course

Do the words Machine Learning or Data Scientist ring a bell? Are you curious about what these techniques are for or why companies around the world pay a data scientist a salary of $ 120,000 to $ 200,000 a year? 
 

Well, this course is thought and designed by a professional in the world of Data Science such as Juan Gabriel Gomila, so that he will share all his knowledge and help you understand the complex theory of mathematics behind it, the algorithms and Programming libraries with Python to become experts, even though you have no previous experience. 
 

We will see step by step on how to start working with concepts and algorithms from the world of Machine Learning. With each new class and section that you complete you will have new skills that will help you understand this world so complete and lucrative that this branch of Data Science can be.
 

Also tell you that this course is very fun, along the lines of Juan Gabriel Gomila and that you will learn and have fun while learning about Machine Learning techniques with Python. In particular, the topics that we will work on will be the following:
 

Part 1 - Install Python and necessary packages for data science, machine learning and data visualization
Part 2 - Historical evolution of predictive analysis and machine learning
Part 3 - Pre-processing and data cleaning 
Part 4 - Data Management and Data Wrangling, Operations with Most Famous Datasets and Probability Distributions
Part 5 - Review of basic statistics, confidence intervals, hypothesis tests, correlation, ...
Part 6 - Simple linear regression, multiple linear regression, and polynomial regression, categorical variables, and treatment of outliers.
Part 7 - Classification with logistic regression, estimation with maximum likelihood, cross-validation, K-fold cross-validation, ROC curves 
Part 8 - Clustering, K-means, K-medoids, dendrograms, and hierarchical clustering, elbow technique and silhouette analysis
Part 9 - Classification with trees, random forests, pruning techniques, entropy, maximization of information
Part 10 - Support Vector Machines for classification and regression problems, nonlinear kernels, facial recognition (how CSI works)
Part 11 - The nearest K neighbors, majority decision, programming Machine Learning algorithms vs Python libraries
Part 12 - Principal Component Analysis, Dimension Reduction, LDA
Part 13 - Deep learning, Reinforcement Learning, Artificial and convolutional neural networks, and Tensor Flow
In addition, in the course you will find exercises, datasets to practice based on real-life examples, so that you will not only learn the theory with the videos but also to practice to build your own Machine Learning models. And how can we not forget that you will have a GitHub with all the Python source code to download and use in all your projects? So don't wait any longer and sign up for the most complete and useful Machine Learning course on the Spanish market!

 

Who this course is for:
Anyone interested in learning Machine Learning
Students who have a knowledge of mathematics who want to learn about Machine Learning with Python
Intermediate users who know the fundamentals of Machine learning such as classical linear regression or logistic algorithms but are looking to learn more and explore other fields of statistical learning
Programmers who like code and are interested in learning Machine Learning to apply these techniques to their datasets
University students looking to specialize and learn to be Data Scientists
Data analysts who want to go further thanks to Machine Learning
Anyone who is dissatisfied with their own job and seeks to start working as a professional Data Scientist
Anyone who wants to add value to their own company using the powerful Machine Learning tools


Basic knowledge
High school math or basic statistical knowledge required
It is recommended to know how to program a little to focus on learning the analysis techniques in Python although it is not totally necessary


What will you learn
Be a Jedi Master of Machine Learning with Python
Carry out accurate predictions
Build robust Machine Learning models
Use Machine Learning techniques for personal use and to advise companies
Have a good intuition of most Machine Learning models
Make very powerful and accurate analyzes
Give added value to your own company or business
Know which Machine Learning model best suits each type of problem
Build diverse Machine Learning models and combine them to solve any problem that arises
Use advanced techniques to reduce the dimension of the problem

 

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