Courses

Given the massive amounts of data that are produced these days, it has become essential that industries adopt data science an integral part of their effort to grow their business, increase customer satisfaction and make better business decisions.  Data science deals with vast volumes of data using modern tools and techniques and complex machine-learning algorithms to identify unseen patterns, derive meaningful information, and inform data-driven business decisions. Data Science depend on several technical concepts such as Machine Learning, Modeling, Databases Statistics and Programming.  This certification program will discuss the foundations of machine learning and data science and will cover data science methodology and explorations and several important topics such as supervised and unsupervised learning models as well as data pre-processing techniques and data visualization.

Course detail:

 

• High-level overview of data science and machine learning
• Data science methodology and data exploration for leaders and managers
• Working with data pre-processing and data visualization - data pre-processing and error estimates, metrics for numeric and categorical data, technical standards, the problem with missing values, estimates of error of regression and classification systems, and techniques for feature extraction and projections
• Unsupervised learning models - market basket analysis, recency-frequency-monetary (RFM) analysis, clustering algorithms (K means, self-organizing maps (SOMs), additional topics on clustering)
• Supervised learning models - decision theory and Bayesian learning systems, learning and classification based on instances, induction of decision trees (general principles, discrete-diffraction-transform (DDT) algorithm, others), ensemble classifiers, neural networks (single perceptron, multi-layer perceptron (MLP), introduction to deep learning neural networks), and support vector machines

Globally there is clear trend that National Statistical Offices (NSOs) are moving from a supply driven approach towards a demand driven, user centric approach. This is seen as a necessity because if NSOs cannot provide what governmental requirements, they will move to source those requirements from private sector companies which can provide what they need. 

Hence, NSO's are running the risk of becoming redundant if they cannot provide what their main users (decision makers in governments) need.  For NSO's this leads to the necessity of deeply understanding the needs of their main users by adapting a user centric approach which is proving to be a huge challenge.
 
This course identifies and provides solutions for the major challenges of moving towards a user centric approach for official statistics. It focuses on maximizing interactions with decision makers to really understand their needs, ranging from sending out questionnaires on users' wishes and requirements, to infrequent meetings to understand their vision and use cases comprehensively.

Course outline:

•    Methodology and Customer Centricity Principles
•    Customer Centricity Tools
•    Building and Maintaining Customer Insights Engines