About Course

Jumpstart your future in GIS with our intensive three-month ArcGIS certificate course, tailored for college students, professionals, and researchers. This course offers a progressive journey from fundamental concepts to advanced applications, equipping you with the skills to convert complex data into actionable insights. As a student, you’ll gain a competitive edge in the job market, while professionals will enhance their expertise for career advancement. Researchers will find valuable tools for conducting in-depth spatial analysis. Enroll today and pave your path in the ever-evolving field of geographic information systems.

Extensive Practical Training: Apply concepts through hands-on exercises.
Expert Instruction: Learn from seasoned GIS and Remote Sensing professionals.
Comprehensive Coverage: Master ArcGIS, Remote Sensing, and DIP techniques.
Job-Ready Skills: Prepare for roles in geospatial analysis and GIS.
Networking: Connect with industry peers and professionals.
Career Boost: Intensive job practice interview session for future opportunities.

Course Content

Introduction to Remote Sensing
A remote sensing instrument collects information about an object or phenomenon within the instantaneous- field-of-view (IFOV) of the sensor system without being in direct physical contact with it.

Basics of remote sensing

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Types of remote sensing

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Remote sensing data sources

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Remote sensing data access on different open access platforms

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Remote Sensing Data Processing
Remote sensing data is generally adjusted and refined through image processing. Image processing techniques, such as filtering and feature detection, are ideal for dealing with the high-dimensionality of geographically distributed systems.

Advanced Mapping Techniques
it's involve using sophisticated methods to analyze and interpret data from sensors and satellites to create detailed maps and models of the environment. These techniques enable researchers and practitioners to extract valuable insights from remote sensing data, supporting applications like land cover mapping, natural resource management, and environmental monitoring.

Data Editing and Topology
Data editing and topology are crucial steps in remote sensing workflows, as they directly impact the accuracy and reliability of downstream analysis, modeling, and decision-making.

Introduction to GIS and ArcGIS
Geographic Information Systems (GIS) enable spatial analysis and mapping, with ArcGIS being a leading software platform. By leveraging GIS concepts and ArcGIS tools, users can unlock valuable insights and make informed decisions.

Working with Spatial Data
Working with spatial data in GIS involves storing, analyzing, and visualizing geographic information with precise location and spatial relationships

Data Management
GIS data management includes data formatting, metadata creation, and database design to support informed decision-making. Effective data management enables efficient data retrieval, updating, and sharing, and is critical for reliable spatial analysis and mapping.

Basic Spatial Analysis
Basic spatial analysis in GIS examines relationships, patterns, and trends in datasets using techniques like buffering and overlay operations to inform decision-making and problem-solving about location, distance, and distribution.

Advanced Spatial Analysis
Advanced Spatial Analysis in GIS employs cutting-edge methods, including spatial modeling, network analysis, and geostatistics, to examine complex geographic relationships and patterns, revealing deeper insights and informed decision-making.

Digital Image Processing
it's involves enhancing and analyzing satellite or aerial images to extract valuable information. Techniques include image correction, filtering, and classification to identify patterns and features.

Independent Project Development
With the instructor's guidance, candidates will develop a minor research-oriented project in their area of interest within remote sensing and GIS. They will present their work to peers, showcasing their research and receiving feedback. At the end of the course, candidates will receive a certificate of completion, recognizing their achievements and skills acquired.

Project Presentation, Certification, and Job Practice

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About Course

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Course Content

Introduction to Remote Sensing A remote sensing instrument collects information about an object or phenomenon within the instantaneous- field-of-view (IFOV) of the sensor system without being in direct physical contact with it.

Basics of remote sensing

Types of remote sensing

Remote sensing data sources

Remote sensing data access on different open access platforms

Remote Sensing Data Processing Remote sensing data is generally adjusted and refined through image processing. Image processing techniques, such as filtering and feature detection, are ideal for dealing with the high-dimensionality of geographically distributed systems.

Image acquisition and pre-processing

Geo-referencing satellite images

Different types of remote sensing (Map to map & Map to Image)

Introduction to image classification

Supervised image classification

Unsupervised image classification

Thematic mapping

Symbolization and labeling

Data Editing and Topology Data editing and topology are crucial steps in remote sensing workflows, as they directly impact the accuracy and reliability of downstream analysis, modeling, and decision-making.

Creating and managing map layouts

Editing spatial data

Ensuring data accuracy and integrity

Q & A and end month assessment of the candidate by quizzes and other activity

Introduction to GIS and ArcGIS Geographic Information Systems (GIS) enable spatial analysis and mapping, with ArcGIS being a leading software platform. By leveraging GIS concepts and ArcGIS tools, users can unlock valuable insights and make informed decisions.

Understanding GIS concepts

Understanding GIS concepts

Overview of ArcGIS interface and tools

Basic mapping and visualization

Working with Spatial Data Working with spatial data in GIS involves storing, analyzing, and visualizing geographic information with precise location and spatial relationships

Types of spatial data (raster vs. vector)

Data sources and acquisition

Importing and exporting data

Organizing spatial data

Data Management GIS data management includes data formatting, metadata creation, and database design to support informed decision-making. Effective data management enables efficient data retrieval, updating, and sharing, and is critical for reliable spatial analysis and mapping.

Geodatabases and shapefiles

Topology rules and error fixing

Polygon related topology error reduction

Polyline related topology error reduction

Basic Spatial Analysis Basic spatial analysis in GIS examines relationships, patterns, and trends in datasets using techniques like buffering and overlay operations to inform decision-making and problem-solving about location, distance, and distribution.

Point feature related topology error reduction

Attribute and spatial queries

Buffering and overlay analysis

Q & A and end month assessment of the candidate by quizzes and other activity

Advanced Spatial Analysis Advanced Spatial Analysis in GIS employs cutting-edge methods, including spatial modeling, network analysis, and geostatistics, to examine complex geographic relationships and patterns, revealing deeper insights and informed decision-making.

Introduction to different reprocessing tools

Metadata and data quality

Introduction to DEM data and related operation

Terrain analysis

Digital Image Processing it's involves enhancing and analyzing satellite or aerial images to extract valuable information. Techniques include image correction, filtering, and classification to identify patterns and features.

Image enhancement techniques

Spectral indices

Raster calculation

Project proposal and planning

Introduction to GPS

GPS data integration in ArcGIS

Q & A and end month assessment of the candidate by quizzes and other activity

Project Presentation, Certification, and Job Practice

Final project presentations

Peer review and feedback

Full fledge industry expert penal Intensive job practice interview session

Continue job practice interview session

Student Ratings & Reviews

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Introduction to Remote Sensing
A remote sensing instrument collects information about an object or phenomenon within the instantaneous- field-of-view (IFOV) of the sensor system without being in direct physical contact with it.

Remote Sensing Data Processing
Remote sensing data is generally adjusted and refined through image processing. Image processing techniques, such as filtering and feature detection, are ideal for dealing with the high-dimensionality of geographically distributed systems.

Data Editing and Topology
Data editing and topology are crucial steps in remote sensing workflows, as they directly impact the accuracy and reliability of downstream analysis, modeling, and decision-making.

Introduction to GIS and ArcGIS
Geographic Information Systems (GIS) enable spatial analysis and mapping, with ArcGIS being a leading software platform. By leveraging GIS concepts and ArcGIS tools, users can unlock valuable insights and make informed decisions.

Working with Spatial Data
Working with spatial data in GIS involves storing, analyzing, and visualizing geographic information with precise location and spatial relationships

Data Management
GIS data management includes data formatting, metadata creation, and database design to support informed decision-making. Effective data management enables efficient data retrieval, updating, and sharing, and is critical for reliable spatial analysis and mapping.

Basic Spatial Analysis
Basic spatial analysis in GIS examines relationships, patterns, and trends in datasets using techniques like buffering and overlay operations to inform decision-making and problem-solving about location, distance, and distribution.

Advanced Spatial Analysis
Advanced Spatial Analysis in GIS employs cutting-edge methods, including spatial modeling, network analysis, and geostatistics, to examine complex geographic relationships and patterns, revealing deeper insights and informed decision-making.

Digital Image Processing
it's involves enhancing and analyzing satellite or aerial images to extract valuable information. Techniques include image correction, filtering, and classification to identify patterns and features.