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Data Scientist Level 3: Machine Learning
Course Outlines
- Introduction to Artificial Intelligence and Machine Learning
- Data Wrangling and Manipulation
- Supervised Learning-Regression
- Feature Engineering
- Supervised Learning-Classification
- Unsupervised learning
- Time Series Modelling
- Ensemble Learning
- Recommender Systems
- Text Mining
What you'll learn
- Master the concepts of supervised and unsupervised learning, recommendation engine and time series modeling algorithms, and applications of Machine Learning.
- Statistical and heuristic aspects of Machine Learning.
- Implement models such as support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-means clustering.
- Improve the performance of Machine Learning models and various accuracy metrics.
- Improve the models with optimization algorithms, which include Boosting & Bagging techniques.
Course Content
- Master the concepts of supervised and unsupervised learning, recommendation engine and time series modeling algorithms, and applications of Machine Learning.
- Statistical and heuristic aspects of Machine Learning.
- Implement models such as support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-means clustering.
- Improve the performance of Machine Learning models and various accuracy metrics.
- Improve the models with optimization algorithms, which include Boosting & Bagging techniques.
Customize a Course
We will be happy to assist you for inquiries about a customized scheduled or program:
Rachael McPherson, Director of Sales
☎(250)882-9549 📧[email protected]
Caroline Santos, Corporate and Custom Sales Manager- Eastern Canada
☎(514)771-3206 📧[email protected]
Course Info
Prerequisites
This course does not require any prerequisites. Just your eagerness to learn!
Duration
20 Hours
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Customize A Course
We will be happy to assist you for inquiries about a customized scheduled or program:
