Learning to work confidently with an analytical instrument is rarely a single event. It is a process that unfolds over time and is shaped by far more than the instrument itself. Modern analytical systems are powerful, flexible, and increasingly software-driven, but that power comes with complexity. Even experienced scientists and engineers often discover that formal education alone does not fully prepare them for real-world operation, troubleshooting, and method adaptation.
This is why training remains one of the most discussed and, at the same time, underestimated aspects of analytical work. Laboratories invest heavily in hardware, service contracts, consumables, and software ecosystems, yet decisions about how people are trained are often made late, inconsistently, or by inertia. As a result, many instruments never reach their full potential. Users follow default workflows without understanding their limitations, troubleshooting becomes slow and reactive, and knowledge remains fragile, tied to individuals rather than embedded in the organization.
There is no universal answer to how training should be organized. Different laboratories, techniques, and teams require different approaches. The goal of this article is not to define a single correct model, but to clarify the landscape: the main types of training, the different kinds of trainers, the often-overlooked role of language, and how to navigate these choices more deliberately.
Why training is more than a formality
In many laboratories, training is treated as a checkbox. A new instrument arrives, a short course is completed, documentation is signed, and routine work begins. Problems emerge later, when something behaves unexpectedly or when the original trained user is no longer available.
Good training does not simply transfer instructions. It builds mental models. It helps users understand what the instrument is doing, how different parameters interact, and where the boundaries of reliable operation lie. This understanding becomes especially important when methods need to be adapted, when samples deviate from the norm, or when results do not look as expected.
Poor or insufficient training rarely causes immediate failure. Instead, it shows up as hesitation, overreliance on service support, conservative use of instrument capabilities, and a general reluctance to explore or optimize. Over time, this quietly reduces efficiency and confidence.
Training formats and where learning actually happens
One of the first decisions laboratories face is the format of training. Each format reflects a different balance between structure, flexibility, and realism.
Training at a dedicated training center remains one of the most common approaches. These courses take place in environments designed specifically for teaching, with standardized instrument setups and carefully planned curricula. Participants are removed from daily laboratory pressures and can focus fully on learning. This format works particularly well for foundational training and for users who are new to a technique or platform.
At the same time, training centers inevitably represent an idealized version of reality. Instruments are clean, configurations are standard, and samples are often simplified. When participants return to their own laboratories, they may discover that applying what they learned requires additional interpretation.
On-site training at the user’s laboratory addresses this gap directly. Working on the actual instrument, with real samples and real constraints, makes the training immediately relevant. Trainers can adapt content to the laboratory’s workflows, identify local issues, and help users connect theory to daily practice. This format is especially valuable for advanced users, method development teams, and laboratories with specialized applications.
The trade-off is that on-site training demands more resources and coordination. Interruptions are harder to avoid, and the quality of the experience depends strongly on both the trainer’s adaptability and the laboratory’s willingness to protect time for learning.
Online training with live participation has become increasingly important, particularly for geographically distributed teams. It allows interaction without travel and can be highly effective for focused topics or experienced users. However, it also depends on stable technical infrastructure and a learning environment free from constant distractions.
Recorded online training offers maximum flexibility. It allows users to learn at their own pace and revisit complex topics. For onboarding, refresher training, or software navigation, recorded material can be extremely useful. Its limitation is the absence of interaction. Without feedback or adaptation, misunderstandings can persist unnoticed. For this reason, recorded training works best as a supplement rather than a complete solution.
Who delivers the training shapes what is taught
The background of the trainer has a profound influence on how training is structured and what it emphasizes.
Training delivered by instrument manufacturers is often the first choice, and for good reason. Manufacturers know their systems in detail, including design decisions, intended workflows, and official best practices. Their training programs are typically well organized and aligned with documentation, software updates, and support structures. For new instruments, manufacturer training is often essential.
At the same time, manufacturer training naturally reflects the manufacturer’s perspective. It may focus on standard use cases and ideal conditions, sometimes leaving less room for unconventional applications or broader cross-platform comparison.
Independent training experts offer a different perspective. Many come from backgrounds as field service engineers, application specialists, or long-term users across multiple laboratories. Their strength lies in practical experience and exposure to a wide range of real-world scenarios. Independent trainers often focus on troubleshooting strategies, workflow optimization, and how instruments behave outside ideal conditions.
Quality in this category can vary widely, making reputation and proven experience especially important when selecting a provider.
Universities and academic institutions represent a third important source of training. Beyond formal degree programs, many universities host specialized courses, workshops, or training “schools” dedicated to specific analytical techniques. These programs often emphasize fundamentals, theory, and method development, and they attract participants from both academia and industry.
Academic training can be particularly valuable for building deep understanding and critical thinking. However, it may be less focused on routine operation or specific commercial configurations. In industrial settings, it often works best when combined with more application-oriented training.
Language and the hidden cost of learning in English
Language is one of the most underestimated factors in training effectiveness. English dominates scientific communication, and many professionals are comfortable reading papers or operating software in English. Training, however, is a different cognitive task.
When the material is complex or entirely new, learning already places a significant cognitive load on the participant. If that load is compounded by the need to process a foreign language, comprehension and retention can suffer. Participants may hesitate to ask questions, miss subtle distinctions, or simply become mentally fatigued.
In such cases, training delivered in the participant’s native language can be significantly more effective. It allows full attention to be directed toward understanding concepts and building confidence, rather than toward translation. This is particularly important for foundational training, safety-related topics, and first exposure to new techniques.
This does not diminish the importance of English-language training. For advanced users, international collaboration, and access to global knowledge, English remains essential. The key is to recognize when language becomes a barrier rather than a benefit, and to choose accordingly.
Finding the right training in a fragmented landscape
Despite the importance of training, information about available options is often fragmented. Manufacturer courses, university programs, independent trainers, and online offerings are scattered across different platforms and networks, making comparison difficult.
To address this, analyte.me provides a dedicated Training Finder that aggregates training opportunities across techniques and regions. The Training Finder allows users to filter available training by country, analytical technique, type of training, and training language. This makes it easier to identify options that match not only technical requirements, but also practical constraints such as location, format, and language preference.
The goal is not to rank or promote specific providers, but to make the training landscape more transparent and navigable for the community.
Training as a continuous process
One of the most common misconceptions about training is that it is a one-time event. Instruments evolve, software changes, methods are adapted, and people leave or change roles. Without ongoing learning, expertise erodes.
Effective laboratories treat training as a continuous process. Initial courses build foundations, while follow-up training deepens understanding and adapts knowledge to new challenges. Online materials, refresher sessions, and advanced workshops all play a role.
Choosing the right training, therefore, is less about finding a perfect course and more about making thoughtful decisions over time, aligned with the laboratory’s goals and reality.
Closing the discussion, not the topic
This topic is not closed, and it is unlikely that a single, universally accepted model of instrument training will ever emerge. Different trainers arrive at different conclusions, shaped by their technical background, teaching experience, and the environments in which they work.
On analyte.me, we intentionally want to make space for these differences. In the coming months, we will publish perspectives from authors representing a range of training approaches, including manufacturer-led programs, independent experts, and academic educators. Not to declare a winner, but to reflect how training actually exists in practice: as a collection of informed, sometimes conflicting viewpoints that the community must navigate on its own terms.