| Attribute | Detail |
|---|---|
| Format | Recorded Lectures |
| Level | Intermediate |
| Duration | 3 Days (60‑90 minutes each day) |
| Certification | e-Certification + e-Marksheet |
| Fee | Free |
| Tools | Python Google Colab Jupyter Notebook Pandas NumPy Matplotlib Scikit‑learn Streamlit Plotly‑Dash |
About the Bioprocess 4.0: AI, Digital Twins & Smart Biomanufacturing Course
Bioprocess 4.0: AI, Digital Twins & Smart Biomanufacturing is a hands‑on course that introduces participants to AI‑enabled bioprocess monitoring, digital‑twin workflows, and smart biomanufacturing systems.
Learn to harness sensor data, machine learning, predictive analytics, and real‑time visualization to boost fermentation performance, yield prediction, anomaly detection, and overall process optimization.
Program Highlights
• Comprehensive coverage of Bioprocess 4.0 from fundamentals to advanced applications
• Hands-on projects and real-world case studies in biotechnology
• Expert-curated curriculum aligned with current industry standards
• Access to recorded lectures and e-LMS platform for flexible, self-paced learning
• e-Certification and e-Marksheet upon successful completion
• Dedicated mentor support and interactive doubt-clearing sessions
• Practical experience with tools: Python, Google Colab, Jupyter Notebook, Pandas
• Career-oriented training for academic and professional growth in biotechnology
Course Curriculum
Module 1: Day 1 – Foundations of Bioprocess 4.0 & Intelligent Monitoring
- Understand Bioprocess 4.0, Pharma 4.0 and smart biomanufacturing concepts
- Explore AI, IoT, sensors and automation roles in biotechnology
- Visualize bioprocess sensor data using Python
- Create a basic real‑time monitoring workflow in Google Colab
Module 2: Day 2 – AI & Machine Learning for Bioprocess Optimization
- Preprocess and engineer features for bioprocess datasets
- Build simple ML models to predict yield, pH, temperature and biomass
- Apply anomaly detection and predictive maintenance techniques
- Optimize fermentation conditions with AI‑driven simulations
Module 3: Day 3 – Digital Twin Implementation & Smart Biomanufacturing Workflows
- Design the architecture of Digital Twin systems for biomanufacturing
- Integrate AI into Digital Twins for real‑time decision support
- Develop interactive dashboards with Streamlit and Plotly Dash
- Explore future trends such as Generative AI, autonomous labs and Industry 5.0
Tools, Techniques, or Platforms Covered
Python Google Colab Jupyter Notebook Pandas NumPy Matplotlib Scikit‑learn Streamlit Plotly‑Dash
Real-World Applications
- Apply Bioprocess 4.0 skills directly to academic research, thesis work, and publications
- Build a professional portfolio showcasing practical biotechnology competencies
- Solve industry-relevant problems using Bioprocess 4.0 methodologies and tools
- Contribute to open-source projects and collaborative research in biotechnology
- Prepare for competitive examinations, interviews, and professional certifications in biotechnology
Who Should Attend & Prerequisites
- Industry‑recognized e‑Certification + e‑Marksheet from NSTC
- Hands‑on training with practical projects and industrial datasets
- Dedicated expert mentorship and doubt resolution
Certification
