This course delves into a range of advanced data analysis practices and analysis techniques that are explored within the context of Big Data. The course content focuses on topics that enable participants to develop a thorough understanding of statistical, modeling, and analysis techniques for data patterns, clusters and text analytics, as well as the identification of outliers and errors that affect the significance and accuracy of predictions made on Big Data datasets.
The following primary topics are covered:
– Modeling, Model Evaluation, Model Fitting and Model Overfitting
– Statistical Models, Model Evaluation Measures
– Cross-Validation, Bias-Variance, Confusion Matrix and F-Score
– Machine Learning Algorithms and Pattern Identification
– Association Rules and Apriori Algorithm
– Data Reduction, Dimensionality Feature Selection
– Feature Extraction, Data Discretization (Binning and Clustering)
– Advanced Statistical Techniques
– Parametric vs. Non-Parametric, Clustering vs. Non-Clustering
– Distance-Based, Supervised vs. Semi-Supervised
– Linear Regression and Logistic Regression for Big Data
– Classification Rules for Big Data
– Logistics Regression, Naïve Bayes, Laplace Smoothing, etc.
– Decision Trees for Big Data
– Tree Pruning, Feature Splitting, One Rule (1R) Algorithm
– Pattern Identification, Association Rules, Apriori Algorithm
– Time Series Analysis, Trend, Seasonality
– K Nearest Neighbor (kNN), K-means
– Text Analytics for Big Data
– Bag of Words, Term Frequency, Inverse Document Frequency, Cosine Distance, etc.
– 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 or visit the Private Training page to learn more about Arcitura’s worldwide private workshop delivery options.
Below are the base materials provided to public and private workshop participants.
Note that as a workshop participant, you may be eligible for discounts on the purchase of the Study Kit and Pearson VUE exam voucher for this course.
Taking the Course using a Study Kit
This course can be completed via self-study by purchasing a Study Kit, which includes the base course materials as well as additional supplements and resources designed specifically for self-paced study and exam preparation.
Visit the BDSCP Module 5 Study Kit page for pricing information and for details. Also, visit the Study Kits Overview page for information regarding discounted Certification Study Kit Bundles for individual certification tracks.
The following materials are provided in the Study Kit for this course:
Taking the Course using an eLearning Study Kit
This course can be completed via self-study by purchasing an eLearning Study Kit subscription, which includes online access to the base course materials as well as additional supplements and resources designed for self-paced study and exam preparation.
Visit the BDSCP Module 5 eLearning Study Kit page for pricing information and details. Also, visit the eLearning Study Kits Overview page for information regarding discounted Certification eLearning Study Kit Bundles for individual certification tracks.
This eLearning Study Kit provides access to the following materials:
Study Kits and Study Bundles can be purchased using the online store. By purchasing and registering this Study Kit, you may be eligible for discounts on the registration of this course as part of a public workshop.
This course is part of the following certification track(s):
– Certified Big Data Scientist
Download a printable PDF document with information about this course module and its corresponding Study Kit.