AI ML in Biology & Bioinformatics Summer Training Program - Work on Real Time Projects + Paper Publication Assistance

Summer Training Program on Artificial Intelligence & Machine Learning (AI ML) in Biology & Bioinformatics + Work on Real-Time Projects

With Paper Publication Assistance

All Participants Under 3 Months & 6 Months of Training Will get a Work Experience Letter

STARTS 22nd APRIL 2024

Welcome to the Summer Hands-On Training on AI and Machine Learning in Biology and Bioinformatics! In the ever-evolving science and technology landscape, the fusion of Artificial Intelligence (AI) and Machine Learning (ML) with Biology and Bioinformatics stands at the forefront of innovation and discovery. This comprehensive training program offers a unique opportunity to delve into the intricate realm where cutting-edge technologies intersect with the complexities of life sciences.

A Roadmap to Success:

Over the course of 15 days, participants will embark on a journey through the fundamentals of AI and ML, tailored specifically for applications in biology and bioinformatics. From understanding the basics of supervised and unsupervised learning algorithms to exploring the depths of deep learning techniques, each unit of the curriculum is designed to provide a comprehensive understanding of the role of AI and ML in biological research. Get to work on real-time projects in 3 Months & 6 Months Training program.

Program Overview

15 Days Training

• Start Date: 22nd April 2024
• Duration: 15 Days
• Timings: 7:00 to 8:00 PM
• Mode: Online
  

3 Months & 6 Months of Training with Real Time Projects & Paper Publication Assistance

• Start Date: 22nd April 2024
• Duration: 3 & 6 Months
• Timings: 5 PM to 6 PM
• Mode: Online

Check Out Complete Details about the Training below:

Scientists Who Will Train You:

• Dr. Nilofer K Shaikh - Biotecnika Global Scientist

• Dr. Prakrity Singh - Computational Biology Scientist

• Mr. Prodyot Banerjee - CADD, Bioinformatics & Genomics Expert

Project Topics Available under 3 Months & 6 Months Training

1. Prediction of protein structure using AI techniques.
2. Identification of potential drug targets using AI-based virtual screening.
3. Predictive modelling of drug side effects using bioinformatics and machine learning.
4. Integration of biological networks for drug repurposing using machine learning.
5. Comparative genomics analysis using machine learning for evolutionary studies.
6. Machine learning classification of microarray gene expression data for cancer subtype identification.
7. Analysis of single-cell RNA sequencing data using unsupervised learning methods.
8. Gene expression analysis using basic ML classification algorithms.
9. Identifying disease-associated genetic variants using supervised learning.
10. Clustering analysis of gene expression data for identifying co-expression modules.
11. Classification of plant species based on leaf morphology using machine learning.
12. Prediction of protein secondary structure using basic supervised learning algorithms.
13. Analysis of gene expression data for disease classification using decision trees.
14. Identification of drug-target interactions using basic bioinformatics and regression models.
15. Development of a simple AI-based model for predicting antibiotic resistance in bacteria.
16. Clustering analysis of microbiome data to identify microbial communities using K-means algorithm.
17. Prediction patient outcome prediction using machine learning classification.
18. Identification of disease-associated SNPs using logistic regression in genomic data.
19. Analysis of protein sequences for subcellular localization prediction using SVM.
20. Differential gene expression analysis using a machine learning algorithm.

Why Attend This Training?

Our training program is meticulously crafted to provide participants with a hands-on learning experience that goes beyond theoretical concepts. Through a combination of expert-led sessions, practical exercises, and real-world projects, attendees will gain the skills and knowledge necessary to excel in this dynamic field. Whether you're a student, researcher, or industry professional, this training offers a gateway to unlocking new opportunities and advancing your career in biology and bioinformatics.

• Hands-On Experience: Gain practical experience through live projects and practical sessions, working with real-world datasets and tools.

• Expert Guidance: Learn from experienced professionals and researchers who specialize in the application of AI and ML in Biology and Bioinformatics.

• Career Enhancement: Acquire sought-after skills that are highly relevant in various industries, including pharmaceuticals, healthcare, biotechnology, and academia.

• Networking Opportunities: Connect with peers, mentors, and industry experts, fostering valuable relationships that can aid in your professional growth.

Course Structure

Curriculum Overview

Unit 1: Introduction to AI and ML in Biology

• Overview of AI and ML
• Applications in Biology & Bioinformatics

Unit 2: Machine Learning in Bioinformatics

• Supervised Learning Algorithms
• Clustering and Dimensionality Reduction
• Unsupervised Learning Applications

Unit 3: Deep Learning in Bioinformatics

• Introduction to Deep Learning
• CNNs and RNNs for Biological Analysis

Unit 4: Data Preprocessing in Bioinformatics

• Python Coding
• Data Cleaning and Handling
• Multi-omics and Genomics Applications

Practical Sessions

• Hands-on Exercises using GitHub Repository
• Utilization of Relevant Tools and Datasets

Role of AI and ML in Biology & Bioinformatics

Artificial Intelligence and Machine Learning have revolutionized the field of Biology and Bioinformatics by enabling the analysis of complex biological data, predictive modeling, and the discovery of novel insights. In this training, you'll explore:

• Data Analysis: Learn how AI and ML techniques can be applied to analyze biological data such as DNA sequences, protein structures, gene expressions, and more.

• Predictive Modeling: Understand the role of supervised learning algorithms in tasks such as sequence classification, protein structure prediction, and drug discovery.

• Pattern Recognition: Explore unsupervised learning techniques for clustering biological data and dimensionality reduction methods for feature selection.

• Deep Learning: Dive into the realm of deep learning with topics like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) for biological data analysis.

Career Prospects

With the increasing reliance on data-driven approaches in biological research and industry, professionals skilled in AI and ML techniques are in high demand. Upon completing this training, you'll be equipped to pursue various career paths, including:

• Bioinformatics Scientist
• Computational Biologist
• Data Analyst/Scientist in Healthcare
• Pharmaceutical Researcher
• Academic Researcher in Life Sciences

Who Can Attend?

This program is ideal for students and professionals in B.Sc., M.Sc., B.Tech., M.Tech., B.Pharm, M.Pharm, Ph.D., and Post-Doc courses related to Life Sciences and Biotech who are keen on expanding their knowledge and skills in AI and ML applications in Biology & Bioinformatics.

Enroll Today and Be Part of the AI ML Revolution in Biology & Bioinformatics

Disclaimer: We do not guarantee paper publication & job placement under this program. We will guide you throughout the training course to ensure you are ready enough to get a job & publish papers in well-reputed journals.