tech club orientation ppt_Technca .pptx

Tech Club Orientatio Program

1. TECHNICAL PROJECT ORIENTATION FOR First Year AI&DS STUDENTS Prepared By, E. Sathesh Abraham Leo/ AP/ADS RMKEC

2. WHY PROJECTS? Classroom Learning focuses mainly on theory, formulas, and algorithms. Knowledge stays in the book unless applied to solve real-world problems. Learning by Doing (Projects) allows students to apply theoretical knowledge to build intelligent systems and data-driven applications. Mistakes and debugging improve understanding and creativity. Example: In class, you learn about classification algorithms. In projects, you apply them to design a spam detection system.

3. WHAT IS A PROJECT? A project is a planned and organized task designed to solve a real-world problem. It applies concepts and techniques from Artificial Intelligence and Data Science. It helps in connecting theory with practical applications . It involves creativity and innovation in developing intelligent solutions. It requires research and analysis to identify the best approach. It focuses on designing, developing, and testing models or systems. It aims to produce measurable and meaningful outcomes . It enhances problem-solving, teamwork, and technical skills . It contributes to learning through experimentation and implementation . It demonstrates the ability to apply knowledge to real-world challenges .

4. Research Projects (AI & Data Science) Research projects focus on solving new or unsolved problems in Artificial Intelligence and Data Science. They aim to explore innovative ideas or improve existing methods and models. Such projects often involve in-depth study, experimentation, and analysis . They help in advancing knowledge in specialized AI/DS domains like deep learning, NLP, or big data analytics. The outcomes may lead to research publications, conference papers, or patents .

5. Social Impact Projects AI-Powered Crop Disease Detection Helps farmers identify diseases in plants using AI-based image recognition. Reduces crop losses and increases productivity. Educational Chatbots Chatbots or apps provide learning support for underprivileged children. Improves literacy and access to quality education.

6. PROBLEM IDENTIFICATION Identify real-world problems in domains Education, healthcare, agriculture, environment, business analytics, or smart systems. EX - Project Title: AI-Based Early Disease Detection System Problem: Many diseases, such as diabetes, heart disease, or cancer, are often detected late, reducing the chances of successful treatment. Manual diagnosis is time-consuming and prone to errors, especially in areas with limited healthcare access.

7. DOMAINS FOR AI & DS PROJECTS 1. Machine Learning & Deep Learning – Fraud detection, disease prediction, recommendation systems. 2. Natural Language Processing – Chatbots, sentiment analysis, language translation. 3. Computer Vision – Face recognition, traffic monitoring, object detection. 4. Data Analytics & Visualization – Predictive analytics, data dashboards, business intelligence. 5. AI for Social Good – Smart waste management, healthcare analytics, energy optimization. 6. Internet of Things with AI – Smart home automation, predictive maintenance, environment monitoring.

8. LITERATURE SURVEY Author(s) and Source: Who conducted the study and where was it published? Year of Publication: When was the study published? Title: What is the title of the study? Methodology: What methods were used in the study (e.g., machine learning algorithms, data analysis techniques)? Dataset: What data was used (e.g., patient records, imaging data)? Results: What were the key findings? Limitations: What limitations were noted by the authors? Key Takeaways: What are the main conclusions or implications of the study? Link/DOI: Provide a direct link or DOI for accessing the full study.

9. LITERATURE SURVEY TABLE TEMPLATE-write in Tabular Column Author Source Year Title Problem Addressed Method/Technology Dataset Results Limitations Key Takeaways Link/DOI

10. STEP 6: DESIGN & PLANNING Block Diagram – Input → Process → Output • Flowchart of Working Selecting Components/Software • Tools First-Year Students Can Use (Arduino, Tinkercad , Python, Proteus) • Planning Timeline – Gantt Chart Example

11. STRUCTURE OF PROJECT REPORT Abstract – Short summary (100–150 words). •Introduction – Problem statement, objectives, scope. •Literature Review – Previous works & gap. •Proposed System / Methodology – Block diagram, flowchart, components. •Implementation & Results – Prototype, data, graphs, photos. •Conclusion & Future Work – Key outcomes, next steps. •References – Proper citation.

12. CONVERTING PROJECT INTO PAPER Once the project is done, you can prepare a JOURNAL paper (10–20 pages). •Benefits: visibility, recognition, and eligibility for grants/hackathons. •Focus only on: problem, novelty, results, and improvement. •Use IEEE/Springer templates (ready-made format)

13. STRUCTURE OF A RESEARCH PAPER Title & Authors – clear, concise. •Abstract – short summary of work (100–150 words). •Introduction – problem background & motivation. •Literature Review – prior works and gaps. •Methodology – your system design, block diagram, flowchart. •Results & Discussion – experiments, graphs, tables, analysis. •Conclusion & Future Work – what you achieved, what’s next. •References – properly cited (IEEE style)

14. Thank You