EncartaLabs

Developing Activity-Based Intelligence (ABI) Applications

( Duration: 5 Days )

The Developing Activity-Based Intelligence (ABI) Applications training course provides the skills needed to become an ABI full-stack developer. This course teaches participants how to quickly turn ABI analysts technical needs into mission-focused software applications.

By attending Developing Activity-Based Intelligence (ABI) Applications workshop, Participants will learn to:

  • Implement entity extraction techniques using Natural Language Processing
  • Standardize and automate the creation of geotemporal and relational metadata sets
  • Apply contemporary analysis techniques to Big Data
  • Implement performant spatiotemporal search strategies

COURSE AGENDA

1

Introduction

  • Principles of effective tactical data science
  • Role of the data science with the intelligence production cycle
  • Core fundamentals of Python
2

File I/O

  • Geospatial data in shapefile and KML file formats using pyshp and fastkml
  • Structured and unstructured text in Microsoft Office and CSV file formats using comtypes and PDFMiner
3

HTTP I/O

  • Finding and accessing RESTful web services
  • Web-scraping and automated page interaction using selenium
4

Stream I/O

  • Creating, publishing and subscribing to message queues using ZeroMQ
  • Joining and posting to IRC channels using Willie
  • Performing Extract, Transform and Load (ETL) Operations
5

Geospatial Transformations

  • Coordinate format conversions between DD, DMS and MGRS using geotrans
  • Geometry type conversions between point, line, and polygon using Shapely
6

Textual Transformations

  • Spatial metadata extraction using OpenSextant
  • Text decomposition and named entity recognition (NER) using elasticsearch
7

Imagery Transformations

  • Mosaics and raster format conversion using GDAL
  • EXIF metadata extraction using exifread
8

Relational Storage Strategies

  • CRUD operations with SQLite
  • Applying full-text indexing using FTS3
  • Implementing geospatial indexing using R*Trees
9

NoSQL storage strategies

  • CRUD operations with MongoDB and Berkeley DB
  • Geospatial and text indexes in MongoDB
10

Statistical analysis methods

  • Linear regression techniques using NumPy
  • Time series analysis techniques using pandas
  • K-means clustering techniques using Scikit
11

Geospatial analysis methods

  • Distance-based buffering and filtering using Shapely
  • Kernel density estimation using Scikit
12

Human network analysis methods

  • Shortest and least-cost path analysis using NetworkX
  • Betweenness and closeness centrality using NetworkX
13

GIS Visualization in QGIS and Google Earth

  • Display vector and raster representations using shapefiles and KMLs
14

Tabular data

  • Creating pivot tables using Microsoft Excel
  • Generating plots and charts using matplotlib
  • Deploying ABI Solutions
15

Client-side deployment

  • Building a Windows stand-alone tool
  • Developing a Python plug-in for QGIS
16

Server-side deployment

  • Creating a simple web interface using SimpleHTTPServer
  • Implementing a RESTful web service using bottlepy

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 4,000 Modules on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

View our other course offerings by visiting http://encartalabs.com/course-catalogue-all.php

Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.

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