Rius Technology

Machine Learning & Deep Learning Course

40h

Course Features:
This Course will refine your skills with the help of topics like Statistics, Trees, and Neural Network etc
and equip you to understand the predictive models of tomorrow with a blink of an eye.
About 40 hours of Instructor Led/Online Training
Projects in Machine Learning & Case studies

Course Objectives:
At the end of the course, one can know how to discover patterns in any given data and then
make predictions based on often complex patterns to answer business questions, detect and
analyse trends and help solve problems.
Labs:
The hands-on will be done, the participants should have adequate permissions to install the required
software on the machine.
Course Outline:

  • This segment will cover the basics of Python and all the tools and libraries required to set up
    a Machine Learning Environment
  • Introduction to Python advanced Python and Machine Learning Tools – SciKit Learn, Pandas,
    Matplotlib, and Introduction to Machine Learning
  • Next section of the course will cover basic algorithms used in Supervised Learning, its
    concepts, maths and projects so that you can practice to code them from scratch
  • Linear Regression, Multivariable Regression and Gradient Descent, Feature Scaling, Logistic
    Regression
  • We will learn about important algorithms like Decision Trees, Random Forests, Naive Bayes,
    KNN and SVM
  • We will continue with advanced algorithms of Supervised Learning in this course and will
    work on the interesting projects. A primer in the supporting concepts of Machine Learning,
    Data Handling, Feature Extraction, Selection and Image Analysis will be provided

Projects

The topics will get you attuned with the applications of Artificial Intelligence and make you
comfortable with its libraries.Neural Networks, Tensor Flow, Keras
Next step we will begin with an introduction to Unsupervised Learning, its application areas, class of
Artificial Neural Networks and Deep Learning. Then, the concept of Clustering, its class and
algorithms will be explained.CNNRNN
Introduction to Unsupervised Learning

Clustering – Flat and HierarchicalK-MeansK-Medoids
Projects:
Price Prediction
Sentiment Analysis
Image Caption Generator
Music Note Generator and more

 

21000 20000

Pre-requisites

  • A Computer Science background is preferred, but not required.

Where to go from here?

  • Interview Preparation Tips
  • Upgrade your skills by learning Julia, Python
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