Skills4Future program is a joint initiative by Edunet Foundation and Shell focussing on Green Technologies and Artificial Intelligence for Faculty from Engineering, Science and Vocational institutions in specified regions of Tamil Nadu, Karnataka, Maharashtra & Gujarat.
The Capacity Building of Faculty program is meticulously designed to equip educators with the necessary skills and knowledge to effectively train the next generation of students.
There is a projected surge in green jobs to 20 million by 2030, thus this program aims to enhance employability and prepare students for emerging career opportunities that are often inadequately addressed by traditional curricula. FDP’s can play a major role in success of the program with handholding & support provided by trained Faculty at institution level.
Faculty Streams:
Engineering
Science
Polytechnics
The Capacity Building of Faculty program is meticulously designed to equip educators with the necessary skills and knowledge to effectively train the next generation of students. Recognizing the pivotal role faculty play in the educational ecosystem, the program focuses on creating long-term impact through the following key elements:
- Hands-On Training: Delivered primarily through classroom settings, the program provides practical, experiential learning opportunities for faculty.
- Comprehensive Training Duration: The program spans 5 days with approximately 25 hours of intensive training, accommodating the availability of teachers while ensuring thorough coverage of essential content.
- Expert Facilitation: Each training session is led by a master trainer, ensuring effective delivery and personalized attention for all participants.
Course offered
Green Technologies and Artificial Intelligence
Mode of Training
Workshop mode through master trainer at your institution
Training Duration
25 hours of training spread across 5 days
FDP Outcome:
- To bridge the industry-academia gap by focusing on the latest technology trends.
- Exposure to different concepts, tools and algorithms in building intelligent systems through experiential learning.
- Learn how to use Python, data analytics tools, libraries to Analyse data and translate data-driven insights into decisions and actions.
- Equip themselves with knowledge in areas of Data Visualization, AI, ML and Power BI.
Program Benefits:
- Certification: Participants will be provided joint certification from Shell and Edunet foundation
- Professional Growth and Development: Participants will acquire advanced teaching methodologies and the latest knowledge in emerging technologies, earning a certification that enhances their professional credentials and recognition.
- Increased Teaching Effectiveness: Engage in hands-on training and gain access to extensive resources, enabling the application of new skills and innovative practices that enhance student engagement and outcomes.
- Long-Term Impact on Educational Institutions: Develop local experts who sustain the program’s impact, create a network for ongoing skill transfer, and support institutions in achieving their educational goals with high-quality teaching.
- Enhanced Knowledge and Skillset: Enhance teaching confidence, foster innovation in pedagogy, and empower faculty to drive positive change within educational institutions.
Program Content:
The program content is carefully curated to address both the technical and pedagogical needs of faculty members. It includes:
Course Outline:
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Sl. No.
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Module
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Units
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Green Skilling and Sustainability
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- Overview of sustainability: Definitions and Importance.
- Green skilling and its importance in the context of sustainability.
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2
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Data Analytics with Python
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- Pandas (Data Manipulation and data analysis)
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3.
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Machine Learning Algorithms
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- Introduction – Machine Learning – Supervised, unsupervised ML
- Linear Machine learning model (linear regression/ logistic regression and it's Evaluation matrices).
- Dimensionality Reduction Techniques (PCA)
- Ensemble Machine learning models
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4.
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Deep Learning
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- Neural Networks – Neurons, Loss Functions, Weights
- Gradient Descent and Back propagation
- Convolutional Neural Network
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5.
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Computer Vision
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6.
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Generative AI and LLM
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- Overview of Large Language Models (LLMs) and their capabilities.
- Exploring pre-trained models like GPT-3/4 and their applications.
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Program Prerequisites:
Hardware requirement:
- Computer /laptop with 1:1 faculty to computer ratio
- Dedicated Classroom / Lab for the session
- High Speed Internet Access with 150 MBPS Speed
- Computers/Desktop with required configuration - 8 GB RAM, Min i3 12th Gen Processor, 256 GB SSD / 512 GB HDD
- Projector or Large Display Screen
Software and tools requirement:
