AI with “Unsupervised” Machine Learning (5 days)
by Walid SemaanLanguages: English
Price (from): €1,500 / day
About the trainer:
Walid Semaan is the founder and president of Matrix TRC "Data Science and AI Academy (partners with the SAS Data Science program). He graduated in engineering from Ecole Supérieure d’Ingénieurs à Beyrouth and holds a degree in finance and marketing from the Ecole Supérieure de Commerce de Paris (ESCP) and an MBA from the University Paris-Dauphine-Sorbonne in Paris. He is the creator and architect of the automated analytical artificial intelligence behind “Triple One Analytics,“ winner of the Best Innovative ICT Project at the 2011 Arab Golden Chip Award. Walid is the trainer of all the workshops he wrote, related to research methodologies, data visualization, data analytics, machine and deep learning, quality control, forecasting, epidemiology and big data ecosystem, as well as mostly used proprietary and open-source data analytical tools. Walid joined lately Fleming Events - Europe as an expert trainer in Data Science and is an expert certified trainer in the Middle East for SAS, PWC Academy, MEIRC-PLUS Training, Abu Dhabi Business School, Formatech and Obeikan Digital College. In parallel, he holds thousands of hours teaching master programs at Saint Joseph University, assisting Ph.D. students in their advanced analytics programs, and training local and international companies, to name few from dozens: Central Bank of Lebanon (Lebanon), PWC (Dubai), Vlerick Business School (Belgium), SCAD (Abu Dhabi), OXY Petroleum (Oman), IPSOS (Lebanon), Obeikan Group (KSA), Dallah Hospital (KSA), Smart Dubai (Dubai), DarkMatter (Dubai), Indevco Industries (Lebanon and Egypt) and Algorithm Pharma (Lebanon).
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AI with “Unsupervised” Machine Learning (5 days) by Walid Semaan
About the training
OVERVIEW
It is very common to have multi-variable data sets describing business topics. But how can we extract all the hidden patterns from within such complex data sets? Reducing with PCA the number of variables into simple “maps”, becomes essential to highlight all those invisible relations within the data, facilitating the correct actions to take. Moreover, this workshop reveals the difference between a scientific market “segmentation” and a simple common sense “filtering”. This empowers the definition of market niches, as well as profiling them with Data Analysis techniques. At the end, the program covers all illustrations that reveal associations between the components of multiple variables for an efficient tracking of patterns evolution. The workshop covers the practical side as well with two different technologies (STATISTICA, SAS), allowing participants to become more consultants than mere experts.
OJECTIVES
By the end of this workshop, you will be able to:
- Explore the rise of AI and technology capacities
- Understanding the definition of exploratory analysis
- Master all “pattern finding” ML algorithms for AI applications
- Mapping data sets of multiple variables in simple charts
- Master differences between all possible “look alike” maps
- Evaluate the quality of reduced variables solutions
- Run professional segmentation with smart clustering
- Investigate the relationship between two sets of variables
- Applications on specialized software solutions
CONTENT
Algebra and Data Analysis essentials
- What is a Matrix
- Additions and Multiplications of Matrices
- Diagonalization of a Matrix
- Essentials of data analysis
Principal Component Analysis
- Observations analysis
- Variables analysis
- Overlaying observations and variables
- Eigenvalues
- Quality of data reduction
Multi-Dimensional Scaling
- Reverse illustration of distances
- Subjective MDS
- Objective MDS
- Evaluating the quality of the MDS map
- MDS vs. PCA
Clustering Analysis
- Clustering logic
- Types of distances and agglomerative rules
- Agglomerative Clustering Process
- Clustering on top of a PCA?
- Non Hierarchical clustering
- K-Means clustering
Quadrant Analysis
- QA in general
- QA for KPIs
- QA for computed variables
- Mixing QAs with Data Analysis
Correspondence Analysis
- Introduction to Chi Square test
- Simple Correspondence Analysis
- Multiple Correspondence Analysis
Main benefits
- #Wide collection of the biggest experts
- #Filters for all kinds of needs
- #User friendly platform
- #Fast and cheap
- #Highest level of proficiency
More trainings of the trainer
Data Visualization and Descriptive Statistics (3 days) Data Analysis for Professionals (5 days) Data Analysis for Experts (3 days) AI with “Supervised” Machine Learning (5 days) Introduction to Deep learning and NLPs for AI applications (3 days) Forecasting Models from A to Z (3 days)