Data-Driven Bioprocess Optimization for Fungal Fermentation
Design of experiments, soft sensors and machine learning to improve titres, yields and consistency in fungal fermentation processes.
Program identification
- 1.1Program name
- Data-Driven Bioprocess Optimization for Fungal Fermentation
- 1.2Type of qualification
- Course
- 1.3Provider / endorsing institution
- Fungaris – International Institute of Mycology, School of Digital Mycology: AI, Genomics & Data. A Fungaris program of its own, not endorsed by a university.
- 1.4Mode of study
- Online, with live sessions in a small group, recordings and a virtual campus.
- 1.5Duration (hours / ECTS credits)
- 3 months (12 weeks) · 72 hours in total · 6 modules of 12 hours · 12 live sessions of 2 hours. ECTS credits: not applicable (Fungaris own program, not an official university degree).
- 1.6Language
- English
- 1.7Start and end dates / intake
- Next intake: January 11, 2027 to April 2, 2027. Enrollment closes on January 4, 2027. Following intake: March 8, 2027. How intakes work →
Overview
2.1Program description
Data-Driven Bioprocess Optimization for Fungal Fermentation brings statistics and machine learning into the fermentation lab. You review the fundamentals of submerged and solid-state fungal processes, then use design of experiments and response surface methods to explore media and conditions efficiently. Process analytical technology and soft sensors show how to estimate hard-to-measure variables in real time, while machine learning and Bayesian optimization help extract more from every run.
Fungal fermentation underpins enzymes, organic acids, pharmaceuticals and the growing mycoprotein sector, and consistency at scale is often the hardest challenge. Data-driven methods reduce the number of experiments needed and make scale-up decisions more transparent. The course suits bioprocess engineers and fermentation scientists with basic statistics. For the final project you plan and analyze an optimization campaign for a fungal process, using supplied or your own data, and present recommendations including what data should travel with the process during tech transfer.
2.2Why it matters / what need it meets
It meets a practical need: applied, up-to-date knowledge in digital mycology, useful in areas such as industrial biotechnology, alternative proteins, enzyme and food ingredient production, pharmaceutical manufacturing.
Mycology is moving fast and good practical training is still scarce. This program gives you a structured path, taught live by people who work in the field, so you can apply what you learn with judgment and safety.
Objectives and competences
3.1General objective
To finish the program able to apply its content professionally and with judgment. In short:
Design of experiments, soft sensors and machine learning to improve titres, yields and consistency in fungal fermentation processes.
3.2Specific objectives
- Build the foundations: Fungal fermentation process fundamentals; Design of experiments and response surfaces.
- Put them into practice: Process analytical technology and soft sensors; Machine learning for process data.
- Apply everything to a real case: Bayesian optimization of media and conditions; Scale-up data and tech transfer.
- Complete a final project reviewed by your instructor.
3.3Competences you will gain
- Describe key variables governing fungal fermentation performance.
- Design and analyze factorial and response surface experiments.
- Develop soft sensors from online process measurements.
- Apply machine learning and Bayesian optimization to process data.
- Prepare structured data packages to support scale-up and tech transfer.
Student profile
4.1Who it is for (entry profile)
Bioprocess engineers and fermentation scientists.
4.2Entry requirements
Experience with fermentation or bioprocessing and basic statistics are expected; coding experience is helpful but not essential.
4.3Career paths (exit profile)
- Bioprocess engineer in fungal fermentation
- Process development scientist in a mycoprotein company
- Data scientist supporting fermentation R&D
- Scale-up and tech transfer specialist
- Process analytical technology engineer
Outcomes depend on your experience and on your local market.
Study plan
5.1Overall structure (modules and workload)
| Module | Title | Phase | Topics | Hours |
|---|---|---|---|---|
| 01 | Fungal fermentation process fundamentals | Foundations | 3 | 12 |
| 02 | Design of experiments and response surfaces | Foundations | 3 | 12 |
| 03 | Process analytical technology and soft sensors | Practice | 3 | 12 |
| 04 | Machine learning for process data | Practice | 3 | 12 |
| 05 | Bayesian optimization of media and conditions | Application & project | 3 | 12 |
| 06 | Scale-up data and tech transfer | Application & project | 3 | 12 |
| Total | 72 |
6 modules × 12 hours = 72 hours: 24 hours of live sessions, and the rest for campus study, exercises and the final project.
5.2Content by module
Hover or tap a module to follow the path from the first session to the final project. Open a module to see the topics it covers.
- Submerged and solid-state fermentation
- Fungal morphology and rheology
- Key process variables and outputs
- Factorial and fractional designs
- Response surface methodology
- Analyzing and visualizing designed experiments
- PAT principles
- Spectroscopic and online sensors
- Building soft sensors
- Preparing batch process data
- Regression and multivariate models
- Interpreting models for process insight
- Gaussian processes
- Acquisition functions
- Running sequential optimization
- Scale-dependent parameters
- Data packages for tech transfer
- Comparing runs across scales
5.3Company placement
This program does not include a company placement. Practice is built into every module through exercises, case studies and the final project.
5.4Final project
A data-driven optimization campaign plan and analysis for a fungal fermentation process, with scale-up recommendations.
Methodology
6.1How it is taught
- Live online sessions, usually weekly, with a working professional and a small group.
- Recordings of every session, so you can catch up if work or time zones get in the way.
- Exercises and real case studies in every module.
- Tutoring: your instructor answers questions and gives feedback on your exercises and project.
6.2Platform and resources
A Moodle virtual campus with session recordings, readings, exercises and forums for each module. You need a computer, an up-to-date browser and a stable connection; a webcam and microphone are recommended.
Technical requirements →6.3Estimated weekly workload
About 6 hours a week for 12 weeks: one 2-hour live session on a weekday evening, plus study and exercises on the campus at your own pace.
Assessment
7.1Assessment system and weighting
Progress is assessed through participation in live sessions, data analysis exercises in each module and a final project reviewed by the instructor.
7.2Requirements to pass
- Complete every module, by attending the live sessions or watching the recordings.
- Hand in the module exercises.
- Have your final project approved by your instructor.
Teaching team
8.1Academic direction
At Fungaris, the Digital Mycology school coordinates the content and quality of this program. The academic director of each intake is named in the intake guide.
8.2Faculty
Taught by professionals who work in the field. The instructor for each intake is confirmed before the start.
Meet our faculty →Certificate
9.1Certificate awarded
Course Certificate
On completing the program and its project, Fungaris issues a Course Certificate. Fungaris certificates are the institute's own. Whether an employer, school or authority recognizes them depends on that organization and on local rules in each country.
9.2Issuing body / recognition
Issued by Fungaris (operated by Nexora Generation, S.L.) as a digital certificate. It is a Fungaris certificate of its own: it is not an official university degree and does not award ECTS credits.
About our certificates →Admission and enrollment
10.1Admission process (steps)
- Send your request through the form or write to admissions.
- Admissions reviews your profile and confirms the start date, the session schedule and the fee.
- You secure your place with full payment or a 40% reservation.
- You receive your campus access and welcome guide before the first session.
10.2Documents required
- A valid identity document.
- Contact and billing details (personal or company).
10.3Deadlines
Enrollment for the intake starting on January 11, 2027 is open until January 4, 2027, or until the group is full (maximum 20 students).
10.4Fee and payment options
Fee: $450
- Full payment before the start: $360 (20% reduction).
- 40% reservation ($180) and 3 monthly installments of $90.
10.5Grants, discounts and funding
Discounts: 10% for Fungaris alumni and 15% for groups of three or more people from the same organization. Discounts cannot be combined with each other or with the full-payment reduction.
Your employer can pay for the program and receive the invoice in the company name. Whether a public or employer training budget can cover the fee depends on your country, so check with them.
10.6Cancellation policy
The conditions for canceling, withdrawing or moving to a later intake are explained in our cancellation policy and in your enrollment confirmation. Nothing there limits your rights under the consumer law that applies to you.
Cancellation and refunds →Additional information
11.1Frequently asked questions
Do I need experience to study Data-Driven Bioprocess Optimization for Fungal Fermentation?
Experience with fermentation or bioprocessing and basic statistics are expected; coding experience is helpful but not essential.
How is Data-Driven Bioprocess Optimization for Fungal Fermentation taught?
Live online, in 6 modules with a working professional, a small group and a final project.
How am I assessed?
Progress is assessed through participation in live sessions, data analysis exercises in each module and a final project reviewed by the instructor.
What is the final project?
A data-driven optimization campaign plan and analysis for a fungal fermentation process, with scale-up recommendations.
What certificate do I get?
On completing the program and its project, Fungaris issues a Course Certificate. Fungaris certificates are the institute's own. Whether an employer, school or authority recognizes them depends on that organization and on local rules in each country.
What can I study after Data-Driven Bioprocess Optimization for Fungal Fermentation?
The natural next step is Diploma in Fungal Bioinformatics.
11.2Alumni testimonials
We only publish verified testimonials from real students. This program does not have any published yet; they will appear here once its first intakes finish.
11.3Admissions contact
Write to info@fungaris.institute or use the contact form. Admissions answers in your language.
Keep branching.
Join the next intake.
Pay in full with a 20% reduction, or reserve your place with 40% and pay the rest in monthly installments. All prices are stated in US dollars (USD).