This course will provide a conceptual overview and practical hands-on experience of a wide range of key tools, techniques and processes used in deep learning and AI.
At the heart of the data mining toolkit is the suite of predictive modelling methods. Accordingly, the course will develop attendees’ literacy in the strengths, characteristics and correct application of a range of predictive modelling methods, from relatively simple linear models through to complex and powerful Random Forests, Support Vector Machines, Decision Trees, Tree Boosting Machines and Neural Networks will be covered along the way. It will also teach the correct framing of predictive modelling problems, suitably preparing data, evaluating model accuracy and stability, interpreting results and interrogating models.
The two key styles of predictive modelling – operational for targeting and explanatory for insights – will be described and distinguished. As well as predictive modelling, the course will cover a range of other key data mining tools, including:
- Data exploration and visualisation: univariate summaries, correlation matrices, heat maps, hierarchical clustering.
- Cluster analysis – used for customer segmentation and anomaly detection
- Other “unsupervised” outlier detection tools.
Tools used
This deep learning and AI course will primarily be taught using Rattle, a graphical interface for predictive modelling and data science in R. Participants will be exposed to “Big Data” techniques as applied to machine learning and deployed on cloud computing platforms. The following additional topics may be covered depending on the pace and interests of the class:
- Link and network analysis visualisation – which provide a simple and compelling way to communicate and analyse relationships, and are commonly applied in forensics, human resources and law enforcement.
- Association analysis – used in retail market basket analysis and the assessment of risk groupings.
- Frequent item set analysis.
See what former trainees are saying about AlphaZetta courses.
Discounts
Face to face public courses: early bird pricing is available until 2 weeks prior. Group discounts: 5% for 2–4 people, 10% for 5–6 people, 15% for 7–8 people, and 20% for 9 or more people. Discounts are calculated during checkout.
Online public courses: available at a 25% off the face-to-face courses as a special introductory price. to groups or to individuals who want to follow a curriculum program and attend multiple courses:
- 2-4 courses/attendees 10% off
- 5+ courses/attendees 20% off
Hurry as bookings will close 1 week before each course. Group discounts are calculated during checkout on individual courses. Individuals can book multiple courses at a discount – please enquire.
Additional Information – Deep Learning and AI
| Audience | Expert This course is suitable for anyone in management, administrative, product, marketing, finance, risk and IT roles who works with data and wants to become acquainted with modern data analysis tools. |
| Prerequisites | Students should have completed or have equivalent knowledge to the courses Fundamentals of AI, Machine Learning, Data Science and Predictive Analytics and Intro to Python for Data Analysis |
| Objective | Attendees should, by the end of the course:
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| Format | Class |
| Duration | 2 days |
| Course Author | Dr Eugene Dubossarsky |
| Trainer | Courses are taught by Dr Eugene Dubossarsky and/or his hand-picked team of highly skilled instructors. |
| Delivery Method | Online, in-person at AlphaZetta Academy locations or on-premise for corporate groups. |
Private and Corporate Training
In addition to our public seminars, workshops and courses, AlphaZetta Academy can provide this training for your organisation in a private setting at your location or ours, or online. Please enquire to discuss your needs.
Scheduled Public Courses
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Private and Corporate Training
In addition to our public seminars, workshops and courses, AlphaZetta Academy can provide this training for your organisation in a private setting at your location or ours, or online. Please enquire to discuss your needs.
Other Data Science Curriculum
Testimonials
Eugene’s courses are not your standard technical courses where you learn how to put data into a model and get a result. The real life experiences – warts and all – he brings to the instruction mean that attendees walk away with a better understanding of the real life challenges of analytics as well as the technical know-how. We routinely send our team members on these courses to help them get the capabilities that really help our clients get better insights from their data.
James Beresford, Director, Agile BIEugene’s introductory course to data science was outstanding. I found the subject matter and delivery fascinating, accessible and informative. Eugene is approachable, interesting to listen to and excellent at simplifying complex concepts. I highly recommend this course for anyone who wants to know what data science—and all the buzz surrounding it!—are all about.
C.T. Johnson, Director, Statecraft