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GICT Certification in Machine Learning
Obtain a Certification in Machine Learning.
Under CITREP+ funding
* Conditions Apply
Courses are delivered by GICT only in Singapore. For other locations, contact our authorised partners directly by clicking here.
What is Machine Learning (ML)?
Machine Learning consist of multiple technologies and techniques, such as deep learning, neural networks and natural-language processing which will trigger autonomous systems that can be programmed to operate independently of humans, allowing IT to go deeper and do more. In other words, ML is an application of artificial intelligence (AI) that allows systems the ability to automatically learn and improve from experience without being programmed. It focuses on the development of computer programs that can access data and use it as learning material for themselves.
Why you should attend a Machine Learning course?
GICT Machine Learning Specialist course will provide participants with an in-depth knowledge on ML algorithms and get skilled using Python. Participants will also be able to experience first-hand leading open-source technologies such as GO, WEKA and SciPy which are implemented by industry leaders such as Google, Oracle, Microsoft etc. Real-cases and industry scenarios on implementation techniques for Machine Learning will also provide Participants with the necessary skills to apply machine learning methods.
Machine Learning certification (ML) programs
Course Outline:
- Unit 1: Introduction and basic concepts in Machine learning
- Unit 2: Introduction to Theories used in Machine Learning
- Unit 3: Supervised learning vs. Unsupervised learning
- Unit 4: Model selection in Machine learning
- Unit 5: Role of Weka in Machine Learning
- Unit 6: Decision Tree and Rule mining using Weka
- Unit 7: A Brief review on SciPy
- Unit 8: Random Forest and Markov Decision Process algorithm
- Unit 9: Google’s Go Programming with k-nearest neighbor’s algorithm
- Unit 10: C 5.0 based decision tree algorithm
Course Outcome
- Learn the fundamentals of AI and machine learning and how it could impact your work through several real-life use case
- Acquire knowledge about Machine Learning techniques/method: Supervised, Unsupervised & Reinforcement Learning through hands-on examples
- Learn key ML concepts like Principle Component Analysis (PCA), Hyperparameter tuning, Clustering, Classification, Regression, Neural Network etc.
- Get skilled in popular machine learning algorithms using Python Programming ( SckitLearn, TensorFlow ), Weka, RapidMiner
Duration
- 32 Hours (4 Days)
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