Postgraduate Diploma in Spectral Capture and Preprocessing
Online 800-hour Postgraduate Diploma in Spectral Capture and Preprocessing. 8 modules covering ASTM E1655, USP and Python with spectral and scikit-learn. Assigned tutor and enrolment open.
Postgraduate Diploma in Spectral Capture and Preprocessing — studying from the United States
Robotics and industrial automation are growing rapidly in the United States, with research centers and companies concentrated in Massachusetts, California, Pennsylvania and Michigan. Manufacturers across automotive, electronics, food processing and logistics deploy robots and control systems to improve productivity and safety. Universities and national programs support advances in collaborative robotics, motion control and AI-driven automation. Engineers work on control theory, sensors, programming and system integration.
Fees for the United States: US$1,670 (US Dollars), with instalments and employer sponsorship available.
Relevant bodies in the United States
Typical roles
Questions from the United States
Which US bodies are relevant to robotics and control engineering?
Key bodies include IEEE, particularly its Robotics and Automation Society, and ISA (International Society of Automation). Industrial safety standards are referenced through A3, the Association for Advancing Automation. Professional PE licensure is issued by state boards where required. SEIUM's private qualifications are not accredited, so employers decide how to value them.
Where do robotics and automation engineers work in the United States?
Employers include robotics companies, automotive and electronics manufacturers, warehouse automation firms, and research labs. Roles include controls engineer, robotics software engineer, and automation specialist. Employers typically assess portfolios, programming skills, and project experience, so build visible work to accompany your qualification.
How much English and time commitment does the programme require?
Programmes are taught fully in English, so strong written and spoken English is needed. They are 100% online, so you study from home without a student visa. Workloads are 300, 800, or 1,900 hours depending on the programme. An assigned technical tutor supports you, and fees can be paid in instalments.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Understand light–matter interaction in the UV, VIS, NIR and SWIR regions.
Select hyperspectral and multispectral imaging systems.
Design online illumination and capture setups.
Calibrate acquisition systems radiometrically and spectrally.
Apply spectral preprocessing techniques such as SNV, MSC and derivatives.
Manage and segment hyperspectral cubes.
Validate spectral capture methods against laboratory references.
Who it's for
- Hyperspectral vision engineer wishing to specialise in Spectral Capture and Preprocessing.
- Chemometrics specialist wishing to specialise in Spectral Capture and Preprocessing.
- Optical instrumentation engineer wishing to specialise in Spectral Capture and Preprocessing.
- Analytical laboratory technician wishing to specialise in Spectral Capture and Preprocessing.
- Process engineer with PAT wishing to specialise in Spectral Capture and Preprocessing.
- Applied spectroscopy researcher wishing to specialise in Spectral Capture and Preprocessing.
- Graduates in engineering or sciences seeking to enter the food sector.
What you'll work with
- ASTM E1655
- USP <1119>
- Ph. Eur. 2.2.40
- ISO 12099
- ASTM E275
- IEC 62471
8 modules · 800 h
1.1UV, VIS, NIR and SWIR electromagnetic spectrum1.2Light–matter interaction: absorption and reflection1.3Diffuse reflectance spectroscopy1.4Absorption bands of organic compounds1.5Raman spectroscopy in industrial control1.6Ultraviolet light-induced fluorescence1.7Laser-induced breakdown spectroscopy (LIBS)1.8Selection of the spectral region1.9Radiation penetration depth1.10Practice: reflectance measurement with a spectrometer
2.1Hyperspectral cubes and their structure2.2Pushbroom and whiskbroom scanners2.3Snapshot multispectral cameras2.4Tunable filters: LCTF and AOTF2.5InGaAs, MCT and CMOS detectors2.6Spatial versus spectral resolution2.7Signal-to-noise ratio and integration time2.8Camera selection by application2.9Mid-infrared imaging systems2.10Laboratory: acquisition with a pushbroom camera
3.1Halogen and broadband LED sources3.2Illumination uniformity3.3Illumination and viewing geometries3.4Specular glare suppression3.5Synchronisation with conveyor belts3.6Source temperature control3.7Industrial inline installation3.8Optical source safety3.9Windows and optical protection on site3.10Workshop: design of a belt capture setup
4.1Wavelength calibration4.2White and dark references4.3Radiometric correction to reflectance4.4Spectralon standards and known reflectance4.5Sensor non-uniformity correction4.6Smile and keystone correction4.7Calibration transfer between instruments4.8Periodic system verification4.9Detector linearity and exposure time4.10Practice: radiometric calibration of a cube
5.1Smoothing with the Savitzky-Golay filter5.2First and second spectral derivatives5.3SNV and MSC correction5.4Baseline removal5.5Normalisation and centring5.6Selection of relevant bands5.7Dimensionality reduction with PCA5.8Detection of anomalous pixels5.9Correction of particle scattering effects5.10Laboratory: comparison of preprocessing methods in Python
6.1Background and object segmentation6.2Specific spectral indices6.3Linear spectral unmixing6.4Pixel-wise chemical maps6.5Regions of interest and averaging6.6Management of large data volumes6.7ENVI and HDF5 formats6.8Compression of hyperspectral cubes6.9False-colour visualisation of cubes6.10Case study: moisture map in grain
7.1Spectral repeatability between measurements7.2Robustness against environmental variation7.3Validation against laboratory reference methods7.4Estimation of spectral uncertainty7.5Qualification of NIR instruments7.6Documentation of the analytical method7.7Equipment maintenance7.8Integration with process control7.9Long-term instrument stability7.10Case study: validation of an online NIR method
8.1Problem definition and samples8.2Selection of spectral technology8.3Setup design8.4System calibration8.5Data acquisition8.6Preprocessing chain8.7Validation of the capture8.8Analysis of results8.9Report and presentation8.10Final review with the tutor
How you'll learn
Fully 100 % online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: students progress at their own pace within the intake, making it compatible with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python with spectral and scikit-learn, ENVI, Solo (Eigenvector), The Unscrambler X, MATLAB, in free, academic or evaluation versions. Case studies cover real hyperspectral capture procedures on sorting belts, NIR analysis of moisture and protein in grain, and radiometric calibration with reflectance standards. Assessment is continuous per module plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Understand light–matter interaction in the UV, VIS, NIR and SWIR regions.
Select hyperspectral and multispectral imaging systems.
Design online illumination and capture setups.
Calibrate acquisition systems radiometrically and spectrally.
Apply spectral preprocessing techniques such as SNV, MSC and derivatives.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient level of Spanish to follow the reading of technical regulations.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme comprises 800 total hours spread over 6 to 8 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
The programme works with Python with spectral and scikit-learn, ENVI, Solo (Eigenvector), The Unscrambler X, MATLAB. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
An SEIUM own diploma upon passing the continuous assessment and the final integrating project. It is in-house training, not an official title from the Ministry.
Yes. Modules passed in a course or postgraduate diploma in the same area count towards the advanced programme. Check the recognition policy when enrolling.
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