API Design & Management

Artificial Intelligence (AI)

Big Data


Business Technology

Cloud Computing




Digital Transformation

Internet of Things (IoT)

Machine Learning


Robotic Process Automation (RPA)

Service Governance

Service Security

Service-Oriented Architecture (SOA)

Spanish Courses & Exams

Arcitura Patterns Site

Arcitura on YouTube

Arcitura on LinkedIn

Arcitura on Facebook

Arcitura on Twitter

Community Home

Arcitura Books Published by Pearson Education

Partner Program

Onsite / Online Exams

Onsite / Online Training

Trainer Development

Home Study Solutions

Contact Arcitura


Workshop Scheduler

Download Catalog (PDF)




Artificial Intelligence Specialist

Big Data Architect

Big Data Consultant

Big Data Engineer

Big Data Governance Specialist

Big Data Professional

Big Data Science Professional

Big Data Scientist

Blockchain Architect

Business Technology Professional

Cloud Architect

Cloud Governance Specialist

Cloud Professional

Cloud Security Specialist

Cloud Storage Specialist

Cloud Technology Professional

Cloud Virtualization Specialist

Containerization Architect

Cybersecurity Specialist

DevOps Specialist

Digital Transformation Data Science Professional

Digital Transformation Data Scientist

Digital Transformation Intelligent Automation Professional

Digital Transformation Intelligent Automation Specialist

Digital Transformation Security Professional

Digital Transformation Security Specialist

Digital Transformation Specialist

Digital Transformation Technology Architect

Digital Transformation Technology Professional

IoT Architect

Machine Learning Specialist

Microservice Architect

RPA Specialist

Service API Specialist

Service Governance Specialist

Service Security Specialist

Service Technology Consultant

SOA Analyst

SOA Architect

SOA Professional

Acclaim/Credly Badges

Pearson Vue Exams



This course provides an in-depth overview of essential and advanced topic areas pertaining to data science and analysis techniques relevant and unique to Big Data with an emphasis on how analysis and analytics need to be carried out individually and collectively in support of the distinct characteristics, requirements and challenges associated with Big Data datasets.

The following primary topics are covered:

  • – Exploratory Data Analysis, Essential Statistics, including Variable Categories and Relevant Mathematics
  • – Statistics Analysis, including Descriptive, Inferential, Covariance, Hypothesis Testing, etc.
  • – Measures of Variation or Dispersion, Interquartile Range & Outliers, Z-Score, etc.
  • – Probability, Frequency, Statistical Estimators, Confidence Interval, etc.
  • – Variables and Basic Mathematical Notations, Statistical Measures and Statistical Inference
  • – Confirmatory Data Analysis (CDA)
  • – Data Discretization, Binning and Clustering
  • – Visualization Techniques, including Bar Graph, Line Graph, Histogram, Frequency Polygons, etc.
  • – Prediction Linear Regression, Mean Squared Error and Coefficient of Determination R2, etc.
  • – Numerical Summaries, Modeling, Model Evaluation, Model Fitting and Model Overfitting
  • – Statistical Models, Model Evaluation Measures
  • – Cross-Validation, Bias-Variance, Confusion Matrix and F-Score
  • – Association Rules and Apriori Algorithm
  • – Data Reduction, Dimensionality Feature Selection
  • – Feature Extraction, Data Discretization (Binning and Clustering)
  • – Parametric vs. Non-Parametric, Clustering vs. Non-Clustering
  • – Distance-Based, Supervised vs. Semi-Supervised
  • – Linear Regression and Logistic Regression for Big Data
  • – Logistics Regression, Naïve Bayes, Laplace Smoothing, etc.
  • – Decision Trees for Big Data
  • – Pattern Identification, Association Rules, Apriori Algorithm
  • – Time Series Analysis, Trend, Seasonality, K Nearest Neighbor (kNN), K-means
  • – Text Analytics for Big Data and Outlier Detection for Big Data
  • – Statistical, Distance-Based, Supervised and Semi-Supervised Techniques

Duration: 1 Day

Taking the Course at a Workshop

This course can be taken as part of instructor-led workshops taught by Arcitura Certified Trainers. These workshops can be open for public registration or delivered privately for a specific organization. Certified Trainers can teach workshops in-person at a specific location or virtually using a video-enabled remote system, such as WebEx.

Visit the Workshop Calendar page to view the current calendar of public workshops.

Visit the Private Training page to learn more about Arcitura’s worldwide private workshop delivery options.

Taking the Course via an eLearning Study Kit

This course can be completed via self-study by purchasing an eLearning study kit subscription, which includes online video lessons, as well as online and offline access to the electronic course materials and additional supplements and resources designed for self-paced study and exam preparation.

Visit the eLearning Study Kits page for more information about eLearning study kits.

Visit the Digital Transformation online store for purchasing information.

Taking the Course via a Printed Study Kit

This course can be completed via self-study by purchasing a printed study kit, which includes the full-color course materials as well as additional supplements and resources designed specifically for self-paced study and exam preparation.

Visit the Printed Study Kits page for more information about full-color printed study kits.

Visit the Digital Transformation online store for purchasing information.


This course is part of the following certification track(s):