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

30 Days Ultimate Training Program on Artificial Intelligence & Machine Learning (AI ML) in Biology, Bioinformatics & Computational Biology 

Work on Real-Time Projects (3 & 6 Months) + Paper Publication Assistance

With Paper Publication Assistance

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

STARTS 12th June 2024

Welcome to our 30-day Summer Training Program on AI & ML in Biology & Bioinformatics - Computational Biology! Explore the synergy between science and technology, delving into AI and ML's applications in understanding biological complexities. Engage in real-time projects and receive guidance for paper publication. Completion of the program earns participants a Work Experience Letter, acknowledging their dedication and proficiency. Join us for an intensive journey into the forefront of AI, ML, and computational biology!

A Roadmap to Success:

Experience a 30-day immersive journey where participants will engage in hands-on projects and explore the dynamic intersection of AI, ML, and biology. Gain insights and skills to tackle complex challenges in genomics, proteomics, and drug discovery.

Program Highlights:

• Real-Time Projects: Work on practical projects to apply AI and ML concepts in biology and bioinformatics.
• Paper Publication Assistance: Receive guidance and support for transforming research findings into impactful publications.
• Work Experience Letter: Participants completing the three-month or six-month training will be awarded a Work Experience Letter.

Join us in this transformative journey, where innovation knows no bounds, and together, let's push the boundaries of possibility in the realm of AI, ML, and computational biology.

Program Overview

30 Days Training

• Start Date: 12th June 2024
• Duration: 30 Days
• Timings: 6:00 to 7:00 PM IST
• Mode: Online
  

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

• Start Date: 12th June 2024
• Duration: 3 & 6 Months
• Timings: 4 PM to 5 PM
• Mode: Online

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. Chemistry candidates with basic understanding of biology concepts can also apply.

Check Out the Complete Details about the Training below:

Scientists Who Will Train You: (Know more about them in the brochure above)

• 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.

Program Curriculum (30 Days): Unit 1: Introduction to AI and ML in Biology

• DAY-1: Overview of AI and ML in Biology (Dr. Nilofer)
• DAY-2: Introduction to Integrated Development Environment (Prodyot Banerjee)
• DAY-3: Introduction to Python (Dr. Nilofer)
• DAY-4: Introduction to R (Dr. Prakrity)
• DAY-5: Data Representation and Visualization (Prodyot Banerjee)
• DAY-6: Importance of AI/ML in Biological Research (Dr. Nilofer)

Unit 2: Machine Learning in Bioinformatics

• DAY-7: Overview of Supervised Learning Algorithms (Prodyot Banerjee)
• DAY-8: Classification and Regression Algorithms (Prodyot Banerjee)
• DAY-9: Clustering Algorithms (Dr. Prakrity)
• DAY-10: Dimensionality Reduction Techniques (Dr. Prakrity)
• DAY-11: Unsupervised Learning Applications (Dr. Nilofer)

Unit 3: Deep Learning in Bioinformatics

• DAY-12: Introduction to Deep Learning (Dr. Nilofer)
• DAY-13: Introduction to Neural Networks (Prodyot Banerjee)
• DAY-14: Convolutional Neural Networks (Prodyot Banerjee)
• DAY-15: Artificial Neural Networks (Dr. Prakrity)
• DAY-16: Recurrent Neural Networks (Dr. Prakrity)

Unit 4: Data Preprocessing in Bioinformatics

• DAY-17: Data Cleaning Techniques (Dr. Nilofer)
• DAY-18: Data Normalization and Feature Selection (Dr. Nilofer)
• DAY-19: Applications of AI/ML in Genomics (Prodyot Banerjee)
• DAY-20: Applications of AI/ML in Proteomics (Dr. Prakrity)
• DAY-21: Applications of AI/ML in Drug Discovery (Dr. Prakrity)
• DAY-22: Applications of AI/ML in Multi-omics (Prodyot Banerjee)

Practical Sessions:

• DAY-22 to 25: Hands-on Exercises using GitHub Repository and Relevant Tools and Datasets (Dr. Nilofer)
• DAY-26: Doubt Solving Session (Dr. Prakrity)
• DAY-27: Open Discussion (Prodyot Banerjee)
• DAY-28 to 30: Project Topic Discussion (Dr. Nilofer, Dr. Prakrity, Prodyot Banerjee)

Role of AI and ML in Biology, Bioinformatics & Computational Biology

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing biology, bioinformatics, and computational biology:

1. Data Analysis: They decipher large biological datasets, revealing patterns and insights beyond human capacity.

2. Prediction: ML models forecast outcomes, aiding drug discovery and personalized medicine by tailoring treatments to individual genetic profiles.

3. Drug Development: Accelerating drug discovery, AI predicts compound efficacy and safety, streamlining development processes.

4. Personalized Medicine: ML tailors treatments to patients' unique genetic and clinical profiles, improving efficacy.

5. Image Analysis: AI automates biological image analysis, enhancing speed and accuracy in microscopy and medical imaging.

6. Network Analysis: Unveiling biological network structures, AI identifies key nodes and pathways, aiding understanding of complex systems.

7. Data Integration: ML integrates diverse biological data types, enriching insights and discoveries across research areas.

In essence, AI and ML empower researchers, accelerating progress and innovation in biological sciences, healthcare, and beyond.

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

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

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.