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1],courseFee:[{description:" Free version : Live webinars are offered free in a Webinar series format on weekend over 10 Sundays.",link:"https://www.meetup.com/disrupt-4-0/events/"},{description:"Paid version : There is a fee for program certification, webinar recordings, and project notebooks."}],certificationFees:[{fee:"USD 100"}],payLinks:[{payLink:"https://buy.stripe.com/7sI4hP02LbmQ4es289"}]},{subtitle:"Starting June 1, 2024",title:"AI Rx: GenAI in Healthcare",beginnerTitle:"Beginner",introLevel:" Introduction Level",intermediateTitle:"Intermediate",advancedLevel:"Advanced Level",backgroundUrl:"/GenAibg2.jpg",beginnerLevel:[{title:"Module 1: Mining Medical Data with Gen AI",desc:"Utilizing AI to mine and analyze vast medical data for insights and patterns.",subtitles:["Understanding Data & its sources","Techniques for preprocessing and ingestion","LLM integration and potential usecases"]},{title:"Module 2: Prompt Engineering for Healthcare",desc:"Tailoring prompts specifically designed for effective application in the healthcare domain.",subtitles:["Introduction to types of Prompting","Applications in Healthcare","Explore different prompting techniques for Medical pipelines"]},{title:"Module 3: Usecase: Insight Generation from Clinical Reports",desc:"Extracting valuable insights from complex clinical reports to enhance decision-making processes.",subtitles:["Understand the business requirements","Data preprocessing","Generative AI integration"]},{title:"Module 4: Natural Language Processing with Named Entity Recognition",desc:"Leveraging natural language processing techniques, including named entity recognition, for precise data analysis.",subtitles:["An Introduction to NLP","Deep dive into NER","Explore healthcare and pharmaceutical workflows of NER"]}],intermediateLevel:[{title:"Module 5: Understanding relationships through Visualizations (Knowledge Graphs)",desc:"Visualizing and understanding intricate relationships within healthcare data through knowledge graphs.",subtitles:["What are Knowledge Graphs?","Applications and usecases","Domain-specific exploration of KG"]},{title:"Module 6: Usecase: Graph prompting for Information Abstraction (Graph RAG)",desc:"Employing graph prompting techniques to abstract and synthesize information for efficient comprehension.",subtitles:["Understand the business requirements","Data preprocessing","Generative AI integration with Graph RAG"]},{title:"Module 7: Vision in Healthcare",desc:"Implementing advanced vision technologies to improve diagnostics and treatment in healthcare.",subtitles:["Understanding imaging data","Explore XRAY-GPT","LLM inferencing for Chest X-ray Analysis"]},{title:"Module 8: Usecase: Adverse event detection",desc:"Employing sophisticated algorithms to detect and address adverse events in medical settings.",subtitles:["Understand the business requirements","Data preprocessing","Generative AI integration"]}],benefits:["Learn from expert Gen AI Scientists","Practice with hands-on projects","Be part of world-class CellStrat AI Lab community","Get product internship and learn to deploy full-stack Gen AI solutions in Healthcare"],handson:[{title:"Hands-on Product Development :-",description:[["Learn by contributing to Product ",{text:"CellBot",url:"https://www.cellbot.ai"}," - a world-class Gen AI Health Platform."],"CellBot is a sophisticated Health Search Engine that mines leading medical repositories for information with Gen AI. It offers an extensive product roadmap for medical and pharma
1workflows in healthcare, pharma research, drug discovery and more."]}],prerequisites:["A basic understanding of Machine Learning and Generative AI is useful. Working professionals, college students as well as Health and Pharma professionals are welcome to attend this program.",{title:"If you need core ML DL or Gen AI training, refer to CellStrat\u2019s",link:"https://cellstrathub.com/course",linkText:"Learn website.",additionalText:"Contact us for more details."}],evaluationMetrics:[{title:"A Certificate of Participation is provided to all enrolled candidates (paid version).",items:[]},{title:" A Certificate of Successful Completion is provided to candidates who pass any of these evaluations :-",items:["Present a webinar on Gen AI topics to CellStrat community","Pass a viva-voce exam (interview)","Publish a research paper in Gen AI for Healthcare"]}],productInternship:[{description:"Top performing candidates will be provided Gen AI Product Internship (unpaid) in CellStrat Health AI Product Team for hands-on experience."}
1],courseFee:[{description:" Free version : Live webinars are offered free in a Webinar series format on alternate weekend over 3 months.",link:"https://www.meetup.com/disrupt-4-0/events/"},{description:"Paid version : There is a fee for program certification, webinar recordings, and project notebooks.",link:"https://www.meetup.com/disrupt-4-0/events/"}],certificationFees:[{fee:"USD 100"}],payLinks:[{payLink:"https://bit.ly/CS-L-HealthAI-pay"}]},{subtitle:"Disrupting with Artificial Intelligence",title:"Post Graduate Certificate in AI and ML",beginnerTitle:"Machine Learning",introLevel:"Basic ML algorithms; 40 hour course (20 hours class videos+ 20 hours of project work)",intermediateTitle:"Deep Learning with TensorFlow",advancedLevel:"Architecting Neural Networks; 40 hour course (20 hours class videos+ 20 hours of project work)",thirdTitle:"Elective(optional)",thirdLevel:"Advanced AI Concepts",fourthTitle:"Generative AI - Foundation Course",fourthLevel:"Gen AI Fundamentals; 40 hour course (20 hours class videos+ 20 hours of project work)",backgroundUrl:"/GenAibg.jpg",beginnerLevel:[{title:"Module 1: Introduction to Artificial Intelligence and Machine Learning"},{title:"Module 2: Maths Review"},{title:"Module 3: Types of learning"},{title:"Module 4: Data Preparation"},{title:"Module 5: Regression"},{title:"Module 6: Classification"},{title:"Module 7: Forms of Unsupervised Learning"}],intermediateLevel:[{title:"Module 1: Introduction to Deep Learning"},{title:"Module 2: Introduction to TensorFlow"},{title:"Module 3: Perceptrons"},{title:"Module 4: How to train Artificial Neural Networks (ANN)"},{title:"Module 5: Gradient Descent and Backpropagation"},{title:"Module 6: Convolutional Neural Networks (CNN)"},{title:"Module 7: Recurrent Neural Networks (RNN)"}],thirdLevelArray:[{title:"NLP"},{title:"Computer Vision"}],fourthLevelArray:[{title:"Module 1: Introduction to Transformers and LLMs"},{title:"Module 2: Prompt Engineering"},{title:"Module 3: Introduction to GPT and LLAMA LLMs"},{title:"Module 4: Understanding Embeddings and Vector Databases and RAG"},{title:"Module 5: Techniques for LLM Fine Tuning"},{title:"Module 6: LLM Application Development with LangChain and LlamaIndex"},{title:"Module 7: LLM Model Evaluation"}],benefits:["Learn from expert AI Scientists","Practice with hands-on projects","Be part of world-class CellStrat AI Lab community","Get product internship and learn to deploy full-stack Gen AI solutions","In-person Contact Sessions with Expert Instructors"],handson:[{title:"Hands-on Product Development:-",description:[["Learn by contributing to CellStrat\u2019s Open Source project ",{text:"LearnView",url:"https://learnview.ai/"}," - Gen AI project to solve for global Educational challenges."]]}],courseDeliveryMode:["All Courses are available as pre-recorded videos in online Learning Management System along with project assignments and project notebooks.","6 Contact Sessions (in-person classes online, 1 hour each) are provided in the course with Expert Instructors."],prerequisites:["Python or any programming language experience is preferred. Both working professionals and college students can do this course in part-time mode.",{title:"If you are expert in ML and DL, you can enroll in ",link:"https://cellstrathub.com/course/gen-ai?cardId=1",linkText:"Generative AI - Foundation",additionalText:"Course."}],evaluationMetrics:[{title:"Candidate must pass any three of these evaluations :-",items:["Present two or more webinars to CellStrat community on ML, DL or Gen AI","Pass a viva-voce exam (interview)","Publish a research paper in ML, DL or Gen AI","Submit at least 4 Classroom assignments in ML and DL courses","Minimum one of the above evaluations must be in domain of Gen AI"]}],productInternship:[{description:"Top performing candidates will be provided Gen AI Product Internship (unpaid) in CellStrat Product Team for hands-on experience."}
1],courseFee:[],certificationFees:[{fee:"USD 799"}],payLinks:[{payLink:"https://buy.stripe.com/9AQbKhaHp3Uo6mAfZ2"}]},{subtitle:"TAILORING PROMPTS FOR OPTIMUM RESULTS",title:"Prompt Engineering for Generative AI",beginnerTitle:"Beginner",introLevel:" Introduction Level",intermediateTitle:"Intermediate",advancedLevel:"Advanced Level",backgroundUrl:"/prompt_bg.png",beginnerLevel:[{title:"Module 1: Introduction to Prompts and Prompt Engineering",subtitles:["Demystifying prompts and their role in LLM interactions.","Defining prompt engineering and its core principles.","Key considerations for prompt design: clarity, conciseness, and direction.","Real-world applications of prompts across various domains (e.g., text generation, translation, code completion)."]},{title:"Module 2: Applications of Prompt Engineering",subtitles:["Prompting for informative text formats (e.g., summaries, reports, emails).","Fine-tuning prompts for specific domains (e.g., legal documents, marketing copy).","Prompting for code completion and generation.","Utilizing prompts for question answering and summarization tasks.","Exploring the potential of prompts for machine translation and image captioning."]},{title:"Module 3: N-Shot, Zero Shot and Few Shot Prompting",subtitles:["Defining N-shot prompting and understanding the variable nature of 'N'.","Understanding the core concept of zero-shot prompting.","Decoding how LLMs leverage pre-trained knowledge for zero-shot tasks.","Examining the challenges and potential limitations of zero-shot prompting (e.g., limited control, potential biases).","Defining few-shot prompting and its role in bridging the gap between zero-shot and full training.","Exploring strategies for selecting effective examples for few-shot prompting.","Discussing techniques for fine-tuning prompts based on the few-shot examples provided."]},{title:"Module 4: Dynamic Prompting with Agents",subtitles:["Introducing the concept of dynamic prompting for real-time adaptation.","Utilizing agents or reinforcement learning to adjust prompts based on LLM outputs.","Applications of dynamic prompting for conversation generation and question answering."]}],intermediateLevel:[{title:"Module 5: Retrieval Augmented Generation (RAG)",subtitles:["Understanding the core idea of RAG: retrieving relevant information and using it for generation.","Integrating external knowledge sources with LLM capabilities for enhanced text production.","Advantages of RAG for factual language tasks and knowledge-based reasoning.","Balancing computational efficiency with responsiveness in dynamic prompting."]},{title:"Module 6: Chain of Thought and Tree of Thought Prompting",subtitles:["Introducing the concept of Chain of Thought (CoT) prompting for reasoning processes.","Guiding the LLM to explain its steps and thought process during generation.","Exploring Tree of Thought (ToT) prompting for more complex reasoning structures.","Addressing the limitations of current explainability methods for LLMs."]},{title:"Module 7: Graph of Thought Prompting",subtitles:["Introducing the concept of Graph of Thought (GoT) prompting for complex knowledge structures.","Utilizing graphs to represent relationships between entities and concepts in the prompt.","Encouraging LLMs to reason and generate text based on the provided knowledge graph."]},{title:"Module 8: Multi-Modal Prompting",subtitles:["Introducing the concept of multi-modal prompting, incorporating various data modalities beyond text.","Multimodal CoT Prompting","Visual Referring Prompting"]}],benefits:["Learn from expert AI Scientists","Practice with hands-on projects","Be part of world-class CellStrat AI Lab community","Get product internship and learn to deploy full-stack Gen AI solutions"],handson:[{title:"Hands-on Product Development :-",description:[["Learn by contributing to CellStrat\u2019s Open Source project ",{text:"LearnView",url:"https://www.learnview.ai"}," - Gen AI project to solve for global Educational challenges."]]}],prerequisites:["Candidates who wish to enroll must be well-versed in Machine Learning and Deep Learning. Both working professionals and college students can do this course in part-time mode.",{title:"If you need ML DL training refer to CellStrat\u2019s ",link:"https://cellstrathub.com/course/gen-ai?cardId=3",linkText:"PG in AI and ML courses",additionalText:"."},{title:"This Prompt Engineering course is a sister course to CellStrat's ",link:"https://cellstrathub.com/course/gen-ai?cardId=1",linkText:"Generative AI - Foundation",additionalText:"course. Both can be done together or separately."}],evaluationMetrics:[{title:"Candidate must pass any two of these evaluations :-",items:["Present a webinar on Gen AI topics to CellStrat community","Pass a viva-voce exam (interview)","Publish a research paper in Gen AI"]}],productInternship:[{description:"Top performing candidates will be provided Gen AI Product Internship (unpaid) in CellStrat Product Team for hands-on experience."}
1],courseFee:[{description:" Free version : Live webinars are offered free in a Webinar series format on alternate weekend over 3 months.",link:"https://www.meetup.com/disrupt-4-0/events/"},{description:"Paid version : There is a fee for program certification, webinar recordings, and project notebooks."}],certificationFees:[{fee:"USD 80"}],payLinks:[{payLink:"https://buy.stripe.com/dR6eWtbLtbmQ4escMR"}]},{subtitle:"STARTING 4TH AUGUST EVERY SUNDAY FOR TWO MONTHS",title:"LLMOps - Operationalizing LLMs - Architecture Design and Deployment",beginnerTitle:"Beginner",introLevel:" Introduction Level",intermediateTitle:"Intermediate",advancedLevel:"Advanced Level",backgroundUrl:"/llmops.png",beginnerLevel:[{title:"Module 1: LLM Foundations and Usage Architecture",subtitles:["Introduction to LLMs and Transformer architecture","Notable LLMs (GPT, T5, BERT, etc.)","Components of LLM-powered applications","Hands-on: Exploring pre-trained LLMs"]},{title:"Module 2: Model Selection and Prompt Engineering",subtitles:["Criteria for choosing the right LLM","Open-source vs. proprietary models","Prompt engineering techniques and best practices","Hands-on: Crafting effective prompts"]},{title:"Module 3: Evaluation, Fine-tuning, and Deployment",subtitles:["Evaluation metrics for LLM performance","Fine-tuning techniques and RLHF overview","Model inference and serving architectures","Hands-on: Setting up a simple LLM API"]},{title:"Module 4: Observability, Monitoring, and Security",subtitles:["Key performance indicators and monitoring tools","Logging and tracing strategies","Security best practices and regulatory compliance","Hands-on: Implementing basic monitoring and security"]}],intermediateLevel:[{title:"Module 5: Agents and Cloud Deployment",subtitles:["Introduction to LLM-powered agents","Tools and platforms for LLM development","Cloud deployment and cost management","Hands-on: Building a simple LLM-powered agent"]},{title:"Module 6: Development Workflow and Case Study",subtitles:["LLM application development lifecycle","CI/CD pipelines for LLM applications","Case Study: Building a Production-Ready LLM Application Notebook","Future trends and closing thoughts"]}],benefits:["Learn from expert AI Scientists","Practice with hands-on projects","Be part of world-class CellStrat AI Lab community","Get product internship and learn to deploy full-stack Gen AI solutions"],handson:[{title:"Hands-on Product Development :-",description:[["Learn by contributing to CellStrat\u2019s Open Source project ",{text:"LearnView",url:"https://www.learnview.ai"}," - Gen AI project to solve for global Educational challenges."]]}],prerequisites:["Candidates who wish to enroll must be well-versed in Machine Learning and Deep Learning. Both working professionals and college students can do this course in part-time mode.",{title:"If you need ML DL training refer to CellStrat\u2019s ",link:"https://cellstrathub.com/course/gen-ai?cardId=3",linkText:"PG in AI and ML courses",additionalText:"."},{title:"This LLMOps course is a sister course to CellStrat's ",link:"https://cellstrathub.com/course/gen-ai?cardId=1",linkText:"Generative AI - Foundation",additionalText:"course. Both can be done together or separately."}],evaluationMetrics:[{title:"Candidate must pass any two of these evaluations :-",items:["Present a webinar on Gen AI topics to CellStrat community","Pass a viva-voce exam (interview)","Publish a research paper in Gen AI"]}],productInternship:[{description:"Top performing candidates will be provided Gen AI Product Internship (unpaid) in CellStrat Product Team for hands-on experience."}
1],courseFee:[{description:" Free version : Live webinars are offered free in a Webinar series format on every weekend over 2 months. ",link:"https://www.meetup.com/disrupt-4-0/events/"},{description:"Paid version : There is a fee for program certification, webinar recordings, and project notebooks."}],certificationFees:[{fee:"USD 100"}],payLinks:[{payLink:"https://buy.stripe.com/eVa9C9aHpez2aCQ3ci"}]},{subtitle:"GET ACCESS TO ALL CELLSTRAT COURSES",title:"CellStrat Learn Subscription",beginnerTitle:"Beginner",introLevel:" Introduction Level",intermediateTitle:"Intermediate",advancedLevel:"Advanced Level",backgroundUrl:"/CellStrat_Learn_Subscription.png",beginnerLevel:[{title:"Module 1: Introduction to Python",subtitles:["Basic Commands","Variables and Types","Strings","Lists","Loops","Functions"]},{title:"Module 2: Machine Learning",subtitles:["Introduction to AI and ML","Data Preparation","How to train Regression models","Classification with Logistic Regression","KNN, Decision Trees and SVMs","Unsupervised Learning with Clustering"]}],intermediateLevel:[{title:"Module 3: Deep Learning",subtitles:["Artificial Neural Networks","Introduction to TensorFlow","How to train multi-layer ANNs","Tuning and Optimizing Neural Networks","Image Processing with Convolutional Neural Networks","Processing sequences with Recurrent Neural Networks"]},{title:"Module 4: Generative AI - Foundation Course",subtitles:["Introduction to Transformers and LLMs","Prompt Engineering","Introduction to GPT and LLAMA LLMs","Embeddings, Vector DBs and RAG","Fine Tuning LLMs","Application Development with LangChain and LlamaIndex","Text to Image and Text to Video","LLM Model Evaluation"]}],benefits:["Learn from expert AI Scientists","Practice with hands-on projects","Access to CellStrat Hub AI platform for learning and practising","Be part of world-class CellStrat AI Lab community","Get product internship and learn to deploy full-stack Gen AI solutions"],handson:[{title:"Hands-on Product Development :-",description:[["Learn by contributing to CellStrat\u2019s Open Source project ",{text:"LearnView",url:"https://www.learnview.ai"}," - Gen AI project to solve for global Educational challenges."]]}],prerequisites:["Both working professionals and college students can do this course in part-time mode. This course is suitable for those candidates who are new to AI and ML. It is also suitable for those who know ML, DL etc. but want to learn Generative AI and LLMs."],courseDetails:[{title:"What does this course include ",description:[["This is self-driven, self-paced course - you get access to all pre-recorded CellStrat courses along with class recordings and project notebooks."],["This course does not include Live Classes."],["If you need AI training via live instructor- led classes, refer to other courses on the ",{text:"CellStrat course page.",url:"https://cellstrathub.com/course"}]]}],evaluationMetrics:[{title:"Candidate must pass any two of these evaluations :-",items:["Present a webinar on relevant AI topics to the CellStrat community","Pass a viva-voce exam (interview)","Publish a research paper in Gen AI"]}],productInternship:[{description:"Top performing candidates will be provided Gen AI Product Internship (unpaid) in CellStrat Product Team for hands-on experience."}
1],courseFee:[{description:" Fee for Certification : USD 20 (for 1 Year Access to courses)",link:"https://buy.stripe.com/eVaeWt6r9gHa5iwaEL"}],certificationFees:[{fee:"USD 20 (for 1 Year Access to courses)"}],payLinks:[{payLink:"https://buy.stripe.com/eVaeWt6r9gHa5iwaEL"}]},{subtitle:"STARTING 16TH NOVEMBER",title:"AI Rx - Accelerating Drug Discovery with Gen AI - Project Series",beginnerTitle:"Beginner",introLevel:" Introduction Level",intermediateTitle:"Intermediate",advancedLevel:"Advanced Level",backgroundUrl:"/llmops.png",beginnerLevel:[{title:"Module 1: Proteins: Software components of Life",subtitles:["Proteins: types, structure, function","Flow of Information in Biological Systems (Central Dogma of Life)","Demonstration of alpha technologies in protein folding, including Google DeepMind\u2019s AlphaFold.","Use Diffusion models to predict protein structure: RFDiffusion"]},{title:"Module 2: Drugs: A boon or a bane",subtitles:["Drugs: Understanding molecules","Transformers basics & their relevance","Common representations of molecules (SMILES, Shorthand descriptors, IUPAC name, Molecular descriptors)","Generative AI for SMILES Generation and Drug-Likeness Evaluation using SwissADMET."]},{title:"Module 3: Understanding data in drug discovery",subtitles:["Explore literature and datasets for Drug discovery.","Explore different types of data (Clinical, Biological, Pharmacological, Toxicology, Genomics & Proteomics, Others [Compliance, regulatory, commercial, computational) ","Autoencoders & their basics.","Chemical Space Representation & process of generating molecules","Implement a Variational Autoencoder (VAE) to generate novel drug-like molecules based on a dataset of known compounds."]},{title:"Module 4: Fundamentals of Drug Discovery",subtitles:["Historical background of drug discovery.","Essential steps in Drug Discovery","Explore traditional and gold-standard processes.","Challenges faced by traditional drug discovery approaches.","Demonstrate how to predict molecular properties such as solubility, toxicity, and biological activity using a machine learning model trained on molecular data."]}],intermediateLevel:[{title:"Module 5: Emerging role of AI in Drug Discovery",subtitles:["Evolution of AI applications in the field of Drug Discovery","Key advantages of AI : speed, cost reduction and enhanced accuracy","Success story of Exscentia\u2019s DSP 1181 in treating OCD patterns","DrugGPT: Discover novel molecules with binding abilities to specific proteins."]},{title:"Module 6: Applications & Considerations of AI",subtitles:["Explore latest techniques (DeepChem, Protein Language Models, Diffusion Models, Antibody Language Models)","Key techniques of machine learning used in Drug Discovery that includes Atomwise, Insilico Medicine, Benevolent AI and Exscientia.","Explainability, Responsibility, Ethics & Regulations around AI.","Fine-tune a language model (e.g., ProtBERT) to generate protein sequences with specific characteristics, like binding affinity."]}],benefits:["Learn from expert Gen AI Scientists","Practice with hands-on projects","Be part of world-class CellStrat AI Lab community","Get product internship and learn to deploy full-stack Gen AI solutions in Healthcare"],handson:[{title:"Hands-on Product Development :-",description:[["Learn by contributing to Product ",{text:"CellBot",url:"https://www.cellbot.ai"}," - a world-class Gen AI Health Platform."],"CellBot is a sophisticated Health Search Engine that mines leading medical repositories for information with Gen AI. It offers an extensive product roadmap for medical and pharma
1workflows in healthcare, pharma research, drug discovery and more."]}],prerequisites:["A basic understanding of Machine Learning and Generative AI is useful. Working professionals, college students as well as Health and Pharma professionals are welcome to attend this program.",{title:"If you need core ML DL or Gen AI training, refer to CellStrat\u2019s",link:"https://cellstrathub.com/course",linkText:"Learn website.",additionalText:"Contact us for more details."}],evaluationMetrics:[{title:" A Certificate of Successful Completion is provided to candidates who pass any of these evaluations :-",items:["Present a webinar on Gen AI topics to CellStrat community","Pass a viva-voce exam (interview)","Publish a research paper in Gen AI for Healthcare"]}],productInternship:[{description:"Top performing candidates will be provided Gen AI Product Internship (unpaid) in CellStrat Health AI Product Team for hands-on experience."}],courseFee:[{description:" Free version : Live webinars are offered free in a Webinar series format on alternate weekend over 3 months.",link:"https://www.meetup.com/disrupt-4-0/events/"},{description:"Paid version : There is a fee for program certification, webinar recordings, and project notebooks.",link:"https://www.meetup.com/disrupt-4-0/events/"}],certificationFees:[{fee:"USD 29.99"}],payLinks:[{payLink:"https://buy.stripe.com/9AQg0x5n54YsdP2eV3"}]},{subtitle:"STARTING 24TH NOVEMBER 9:30 AM IST, ALTERNATE SUNDAYS",title:"Gen AI for Healthcare Professionals",beginnerTitle:"Beginner",introLevel:" Introduction Level",intermediateTitle:"Intermediate",advancedLevel:"Advanced Level",backgroundUrl:"/llmops.png",beginnerLevel:[{title:"Module 1: Evolution of AI",subtitles:["Historical account of artificial intelligence","Exploring artificial neurons & backpropagation.","Key concepts & definitions.","Current Landscape of AI in Healthcare"],caseStudy:"LLM Essentials: Using ChatGPT and CellBot for Conversational AI in Healthcare"},{title:"Module 2: Data based Decision Making",subtitles:["Data Types and their computational representations.","Data Sources in Healthcare","Data processing and analytics","Supervised, unsupervised, and reinforcement learning."],caseStudy:"LLM Essentials: Analyze sample datasets for different use cases (Using CellStrat\u2019s KB Miner)"},{title:"Module 3: Architecting Generative AI in Healthcare",subtitles:["Models: definition and types","Basic architecture: transformers","Need for vectorization: embeddings and their importance","Applications (RAG, Agents, LLMs, Vision, Audio)"],caseStudy:"LLM Essentials: Summarize Patient Notes, History, and Lab Reports using LLMs."},{title:"Module 4: Evaluation and Validation of AI Systems",subtitles:["Understanding the key metrics for assessing fairness & usefulness (accuracy, sensitivity & specificity).","Ethical considerations (Responsible & Explainable AI)","Regulatory Landscape of AI.","Future Implications and trends."],caseStudy:"Evaluate the performance of a pre-built diagnostic AI tool using real-world metrics and create a report on its ethical implications."}],intermediateLevel:[{title:"Module 5: Applications of GenAI in Healthcare ",subtitles:["Diagnostic tools using AI (image analysis, predictive algorithms).","Treatment planning and personalized medicine.","AI in operational workflows, such as patient management and hospital logistics.","Future trends in AI-enabled drug discovery and healthcare operations."],caseStudy:"Build a prototype using a no-code AI tool to analyze patterns in patient data and make basic predictions."}],benefits:["Learn from expert Gen AI Scientists","Practice with hands-on projects","Be part of world-class CellStrat AI Lab community","Get product internship and learn to deploy full-stack Gen AI solutions in Healthcare"],handson:[{title:"Hands-on Product Development :-",description:[["Learn by contributing to Product ",{text:"CellBot",url:"https://www.cellbot.ai"}," - a world-class Gen AI Health Platform."],"CellBot is a sophisticated Health Search Engine that mines leading medical repositories for information with Gen AI. It offers an extensive product roadmap for medical and pharma
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1ollaborative, role-based agent systems.","Implement advanced frameworks to solve complex problems","Learn to combine advanced and core frameworks effectively."],caseStudy:"Implement a multi-agent system using AutoGen and CrewAI."},{title:"Module 6: Testing and Validation of AI Agents",subtitles:["Learn testing strategies for AI agents to ensure reliability and performance.","Understand unit testing, integration testing, and validation techniques.","Apply testing frameworks and tools specific to AI agents.","Incorporate continuous testing in development workflows."],caseStudy:"Write and execute tests for AI agents developed in previous modules."},{title:"Module 7: Evaluation and Observability of AI Agents",subtitles:["Evaluate AI agent performance using practical, real-world metrics.","Monitor agent workflows and system behaviors using observability tools.","Optimize agent performance through iterative profiling and tuning.","Plan effective deployment strategies for production environments."],caseStudy:"Set up observability tools to monitor and analyze AI agent performance."},{title:"Module 8: Ethics and Responsible AI in Depth",subtitles:["Deepen understanding of ethical considerations in AI agent development.","Explore bias mitigation techniques and fairness in AI.","Understand regulatory compliance and responsible AI practices."],caseStudy:"Analyze AI agent designs for ethical considerations and propose improvements."},{title:"Module 9: Case Studies and Industry Applications",subtitles:["Analyze real-world case studies to understand the application of AI agents in industry.","Discuss challenges faced and solutions implemented in deploying AI agents.","Learn from successes and failures to inform best practices."],caseStudy:"Collaborative analysis of case studies, identifying key insights and takeaways."}],benefits:["Learn from expert Gen AI Scientists","Practice with hands-on projects","Be part of world-class CellStrat AI Lab community","Get product internship and learn to deploy full-stack Gen AI solutions in Healthcare"],handson:[{title:"Hands-on Product Development :-",description:[["Learn by contributing to Product ",{text:"CellBot",url:"https://www.cellbot.ai"}," - a world-class Gen AI Health Platform."],"CellBot is a sophisticated Health Search Engine that mines leading medical repositories for information with Gen AI. It offers an extensive product roadmap for medical and pharma
1workflows in healthcare, pharma research, drug discovery and more."]}],prerequisites:["Candidates who wish to enroll must be well-versed in Machine Learning and Deep Learning. Both working professionals and college students can do this course in part-time mode.",{title:"If you need ML DL training refer to CellStrat\u2019s ",link:"https://cellstrathub.com/course/gen-ai?cardId=3",linkText:"PG in AI and ML courses",additionalText:"."},{title:"This Agentic AI course is a sister course to CellStrat's ",link:"https://cellstrathub.com/course/gen-ai?cardId=1",linkText:"Generative AI - Foundation",additionalText:"course. Both can be done together or separately."}],evaluationMetrics:[{title:" A Certificate of Successful Completion is provided to candidates who pass any of these evaluations :-",items:["Present a webinar on Gen AI topics to CellStrat community","Pass a viva-voce exam (interview)","Publish a research paper in Gen AI"]}],productInternship:[{description:"Top performing candidates will be provided Gen AI Product Internship (unpaid) in CellStrat Health AI Product Team for hands-on experience."}
1],courseFee:[{description:"Free version : Live webinars are offered free in a Webinar series format every weekend over 3 months.",link:"https://www.meetup.com/disrupt-4-0/events/"},{description:"Paid version : There is a fee for program certification, webinar recordings, and project notebooks.",link:"https://www.meetup.com/disrupt-4-0/events/"}],certificationFees:[{fee:"USD 100 (Use Coupon Code COMM40 to get 40% discount)"}],payLinks:[{payLink:"https://buy.stripe.com/fZedSpg1J8aE26k9AK"}]},{subtitle:"STARTING 22ND MARCH 2025 SATURDAY, EVERY ALTERNATE WEEKEND",title:"Generative AI in Bioinformatics",beginnerTitle:"Beginner",introLevel:" Introduction Level",intermediateTitle:"Intermediate",advancedLevel:"Advanced Level",backgroundUrl:"/llmops.png",beginnerLevel:[{title:"Module 1: Introduction to Generative AI in Bioinformatics",subtitles:["Overview of Generative AI and its relevance in Bioinformatics.","Evolution of AI in computational biology.","Key architectures: VAEs, GANs, Diffusion Models, Transformers.","Tools Covered: AlphaFold, RoseTTAFold, ESMFold","Plan of Action: Use a publicly available protein sequence, run it through ESMFold, visualize the structure, and compare RMSD values with AlphaFold predictions."],caseStudy:"Using ESMFold for protein structure prediction : Predict the 3D structure of a disease-related protein using ESMFold and compare its accuracy with AlphaFold. "},{title:"Module 2: AI-Driven Genomic Data Analysis ",subtitles:["Role of Generative AI in genomic sequence analysis","AI-based genome annotation and variant detection ","Synthetic genome generation and mutation simulation ","Tools Covered: DeepVariant, DeepSignal, GenSLM ","Plan of Action: Process raw sequencing reads, run DeepVariant for variant calling, and compare detected mutations with known pathogenic variants."],caseStudy:"Variant calling using DeepVariant : Analyze whole-genome sequencing data with DeepVariant to identify disease-associated mutations in a cancer dataset."},{title:"Module 3: AI in Structural and Functional Proteomics ",subtitles:["AI-generated protein structure and function predictions. ","AI-assisted protein docking and interactions.","Predicting post-translational modifications.","Tools Covered: OmegaFold, DiffDock, ProtGPT2","Plan of Action: Select a protein-ligand pair from a public database, run docking simulations using DiffDock, and evaluate binding pose accuracy with experimental structures."],caseStudy:" Molecular docking using DiffDock : Use DiffDock to predict ligand binding poses for a target protein and validate results against experimental data. "}
1,{title:"Module 4: AI in Synthetic Biology and Metabolic Engineering",subtitles:["Designing synthetic biological pathways using AI ","AI-assisted enzyme engineering for metabolic pathway optimization","Generating synthetic DNA sequences for protein engineering","Tools Covered: CodonGenie, ProteinMPNN, AI-generated Biosensors","Plan of Action: Take an existing enzyme sequence, modify key residues using ProteinMPNN, analyze stability using molecular dynamics simulations, and compare with wild-type performance."],caseStudy:"AI-driven enzyme optimization using ProteinMPNN. Design an optimized enzyme sequence for industrial biocatalysis using ProteinMPNN and assess stability improvements."}],intermediateLevel:[{title:"Module 5: AI-Powered Multi-Omics Data Integration",subtitles:["Combining genomics, transcriptomics, proteomics, and metabolomics.","AI in single-cell analysis and biomarker discovery.","Predicting phenotypic traits from multi-omics data","Tools Covered: scGen, Cell2Cell, BioGPT","Plan of Action: Process single-cell RNA-seq data, use Cell2Cell to map cell-type interactions, and generate network visualizations highlighting key signaling pathways."],caseStudy:"Cell-cell interaction modeling using Cell2Cell. Investigate tumor microenvironment interactions using single-cell RNA-seq data and visualize cell signaling pathways."},{title:"Module 6: Future Trends and Ethical Considerations in AI-Bioinformatics",subtitles:["AI in personalized medicine and computational pathology.","Ethical challenges in AI-generated biological data. ","Integration of AI with wet-lab experiments for enhanced predictions.","Tools Covered: BioBERT, ChatGPT-Bio, Generative AI in Clinical Genomics","Plan of Action: Input biomedical text datasets, fine-tune BioBERT for named entity recognition, extract disease-gene relationships, and compare with existing databases. "],caseStudy:"AI-assisted clinical genomics using BioBERT Extract disease-gene associations from biomedical literature using BioBERT and validate findings with known datasets."}],benefits:["Learn from expert Gen AI Scientists","Practice with hands-on projects","Be part of world-class CellStrat AI Lab community","Get product internship and learn to deploy full-stack Gen AI solutions in Healthcare"],handson:[{title:"Hands-on Product Development :-",description:[["Learn by contributing to Product ",{text:"CellBot",url:"https://www.cellbot.ai"}," - a world-class Gen AI Health Platform."],"CellBot is a sophisticated Health Search Engine that mines leading medical repositories for information with Gen AI. It offers an extensive product roadmap for medical and pharma
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