Why Study Machine Learning?
Covering the essentials for learners to work on Machine Learning and AI projects at IT companies by the end of the program
Widely beneficial to professionals in multiple fields from IT to Economics, Banking and Fintech
Highly practical program with 70% lab and project time
Can be completed in 30 weeks (2-3 hours of study/day) or shorter depending on learner’s preference and abilities
Capstone Project involving the application of Machine Learning to solve a problem companies are facing
1:1 live coaching and unlimited Q&A sessions with industry mentors
Advising on building effective study plans and habits
Weekly xTalk with experts and managers on hottest topics of technology & industry
Post-program career coaching
Internship and employment referrals
Who is This Program For?
The Machine Learning (ML) Program is suitable for everyone who wants to learn and work in the field of Artificial Intelligence (AI) and wants to become an ML/AI Engineer, especially for:
Entry Requirements:Prior to starting the Machine Learning Program, learners should know the following:
What You Will Learn...
110 hour to complete
COURSE DESCRIPTION Deep learning can be considered as a subset of machine learning which improves on its own by examining...
41 hour to complete
COURSE DESCRIPTION Within Machine Learning problems, those of unsupervised learning such as Clustering and Retrieval remain the hardest to resolve...
59 hour to complete
COURSE DESCRIPTION Machine Learning Classification is one of the most popular research areas in the machine learning field. In this...
43 hour to complete
COURSE DESCRIPTION Regression is a large subset of Machine Learning problems that involves predicting a numerical value using known variables...
55 hour to complete
COURSE DESCRIPTION Machine learning is the application of artificial intelligence (AI) that allows machines to automatically learn and improve without...
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Voice of Learners & Partners
“Only at FUNiX did I see a clear roadmap to work in AI. My previous knowledge is quite fragmented and shallow. After the course, I understood much better about Machine Learning algorithms. I also practiced with real projects, worked and exchanged with experienced mentors and developed effective self-study skills. Thanks to the encouragement of my student success advisor and others, I studied a little bit everyday and finally made it to the end. During my capstone project, I had to stay up overnight for two or three days to monitor my product. Sleep-deprived, but the passion and feeling of conquering knowledge and completing the program excited me. The mentors showed me many things that in the working world not a lot of people would, such as work advice and techniques to handle technical problems in the field of Artificial Intelligence. I am particularly impressed with mentor Hai Nam and mentor Quy. Mentor Quy is always meticulous and seems to know what I’m not understanding, then step by step encourages me to speak out and explains to me carefully. Mentor Nam works closely with me, always sets strict requirements and demands, thereby making me study thoroughly each issue. He helps me have a vision of work performance and form a scientific and detail-oriented way of working.”