AI For Space Application Training Program

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Ai for Space Application

Don't wait, Enroll Now →

₹3,999

₹1,999

Ai for Space Application Traning Program

Unlock the immense potential of artificial intelligence in revolutionizing the space industry

Starting from 11th January to 8th February

Mentors

Arya Pratap Singh

ML Researcher-2, KaleidEO

Anuj Soni

Project Intern, NRSC ISRO

Ai for Space Application Training Program

Unlock the immense potential of artificial intelligence in revolutionizing the space industry

11th January to 8th February

Now at

₹1,999

₹3,999

Don't wait, Enroll Now →

1000+ learners

Have benefitted

Instant access

right after enrolment

Our alumni work at top companies in the world

upskill and unlock your career potential

Live session

OnDemand session

Top industry mentors

will guide you through this

Detailed Curricullum

Remote Sensing & Data Preprocessing

ML, DL & algorithms implementation

AI with GIS & DL algos

Live project work

Module 1

Introduction to Remote Sensing

Fundamentals of remote sensing: History, platforms, and sensors

Types of remote sensing (active vs passive, optical vs radar).

Key terminologies: Spatial, spectral, temporal, and radiometric resolution.

Overview of remote sensing data sources: Satellites, drones, and aerial systems.

Hands on

Module 2

Remote Sensing Data Preprocessing

Data formats (GeoTIFF, HDF, NetCDF) and tools (QGIS, GDAL).

Data cleaning, radiometric, and atmospheric corrections.

Image registration, resampling, and mosaicking techniques.

Cloud removal and noise reduction.

Hands on

Module 3

Introduction to ML and DL

Types of algorithms

Current trends in AI

Thinking from an algorithm’s perspective Basic hands on exercise for data preparation.

How to do EDA?

Module 4

Hands on algorithms implementation

Introduction to sk-learn, tensorflow/pytorch

Classification using ML algorithms

Introduction to CNNs, LSTMs, GANs, Autoencoders

Hands on

Module 5

Integrating AI with GIS and its Application in RS

Role of Geographic Information Systems (GIS) in remote sensing.

AI integration with GIS: Geospatial data analysis, visualization, and interpretation.

AI applications in agriculture, forestry, urban planning, and disaster management.

Real-world use cases of AI-powered remote sensing (crop monitoring, deforestation tracking, flood mapping).

Hands on

Implementing AI-based remote sensing projects for specific applications (agriculture, urban planning, etc.).

Module 6

Advanced Deep Learning algos

Implementing ANNs, CNNs, Unet.

Introduction to edge computing and parallel computing.

Basic introduction to foundation models.

Module 7

Live Project work

Introduction to hugging face models

Pulling weights of large pre-trained models and training live.

Comparing model accuracy (Vanilla and pre-trained)

Doubt Session

This is built for

Undergraduates

Gain foundational knowledge and hands-on experience in AI and space tech integration.

Professionals

Upgrade your expertise in geospatial analysis and artificial intelligence applications.

Entrepreneurs

Build AI-powered solutions for industries like agriculture, disaster management, and urban planning

Researchers

Leverage AI to address complex challenges in remote sensing and data analysis

About your program directors

Key Learnings

Master the fundamentals of remote sensing, including data acquisition and visualization.
Gain expertise in preprocessing techniques for multispectral and hyperspectral imagery.
Understand and implement AI algorithms like CNNs, LSTMs, and Autoencoders for space applications.
Integrate AI with GIS for geospatial data analysis and practical industry use cases.
Learn cutting-edge concepts like edge computing, foundation models, and advanced deep learning.
Receive personalized mentorship and guidance to create impactful AI-powered solutions.

Benefits of Our Certification:

1. Boost your career prospects with a certification acknowledged across the world.
2. Improves chances of employment and career advancement.
3. Ensures top-quality education and training.