[{"data":1,"prerenderedAt":76},["ShallowReactive",2],{"guide:kurumsal-yapay-zeka-egitimi-nasil-secilir:en":3},{"id":4,"title":5,"slug":6,"excerpt":7,"cover_image_url":8,"published_at":9,"reviewed_at":10,"body":11,"seo_title":12,"meta_description":12,"faq":13,"related_trainings":29,"updated_at":75},1,"How to choose corporate AI training?","kurumsal-yapay-zeka-egitimi-nasil-secilir","A step-by-step guide outlining what to consider when selecting corporate AI training—from setting goals and role-based content to data security and impact measurement.","https:\u002F\u002Facademyclub.b-cdn.net\u002Fguides\u002F24a2f25fd1784c198230aaebdc54e7bb.webp","2026-10-14T11:37:33.243221+03:00","2026-10-14","\u003Ch2>Short answer\u003C\u002Fh2>\u003Cp>Corporate AI training is selected by first clarifying which business outcome the training will serve and who will participate; the decision on tools or providers comes afterward. The right program is one that is segmented according to participants’ roles, includes hands-on practice using the organization’s own processes, covers data security rules, and measures results through behavioral change at work. Whether the trainer has applied the subject in the field matters more than the title in a catalog.\u003C\u002Fp>\u003Ch2>Core concepts\u003C\u002Fh2>\u003Cp>\u003Cstrong>Generative AI:\u003C\u002Fstrong> The general term for AI systems that produce new content such as text, code, images, or audio.\u003C\u002Fp>\u003Cp>\u003Cstrong>Large Language Model (LLM):\u003C\u002Fstrong> A model trained on vast amounts of text data that answers questions and generates text in natural language.\u003C\u002Fp>\u003Cp>\u003Cstrong>Prompt engineering:\u003C\u002Fstrong> The deliberate structuring of instructions, context, and examples to obtain consistent and accurate output from a model.\u003C\u002Fp>\u003Cp>\u003Cstrong>RAG (Retrieval-Augmented Generation):\u003C\u002Fstrong> An architecture in which the model retrieves relevant pieces from the organization’s own documents and uses them as context before generating a response.\u003C\u002Fp>\u003Cp>\u003Cstrong>AI agent:\u003C\u002Fstrong> An LLM-based system that plans its own steps to reach a goal, calls tools, and continues based on the results.\u003C\u002Fp>\u003Cp>\u003Cstrong>AI literacy:\u003C\u002Fstrong> Employees’ ability to make decisions knowing what AI tools can do, where they make mistakes, and with which data they must not be used.\u003C\u002Fp>\u003Ch2>What should the first decision be when choosing corporate AI training?\u003C\u002Fh2>\u003Cp>The first decision is which business outcome the training will change and whose behavior will drive that change; the choice of topic and provider comes after this decision. “Our employees should learn AI” is an intention, not a goal. The goal should be an observable change such as “software teams should use an assistant during code review.”\u003C\u002Fp>\u003Cp>When writing the goal, answer three questions:\u003C\u002Fp>\u003Cul>\u003Cli>\u003Cp>\u003Cstrong>Who:\u003C\u002Fstrong> Which role or team, how many people, and what is their current knowledge level?\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>What will change:\u003C\u002Fstrong> Which task will they perform differently after the training?\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>How will it be verified:\u003C\u002Fstrong> Which observation or metric will show this change three months later?\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Cp>If you cannot give clear answers to these questions, start with a short needs analysis or a pilot group study instead of rolling out a company-wide program.\u003C\u002Fp>\u003Ch2>Which team needs which type of AI training?\u003C\u002Fh2>\u003Cp>Every team needs training of different depth and content; giving the same program to the whole company either bores technical teams or leaves business units behind.\u003C\u002Fp>\u003Ctable>\u003Ctbody>\u003Ctr>\u003Cth colspan=\"1\" rowspan=\"1\">\u003Cp>Target group\u003C\u002Fp>\u003C\u002Fth>\u003Cth colspan=\"1\" rowspan=\"1\">\u003Cp>Learning goal\u003C\u002Fp>\u003C\u002Fth>\u003Cth colspan=\"1\" rowspan=\"1\">\u003Cp>Typical content\u003C\u002Fp>\u003C\u002Fth>\u003Cth colspan=\"1\" rowspan=\"1\">\u003Cp>Suitable duration range\u003C\u002Fp>\u003C\u002Fth>\u003C\u002Ftr>\u003Ctr>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Senior management\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Being able to make investment and risk decisions\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Use cases, cost, risk and governance\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Half a day – 1 day\u003C\u002Fp>\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Business units\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Using the assistant safely and efficiently\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Tool usage, prompt writing, output verification, data rules\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>1 – 2 days\u003C\u002Fp>\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Software teams\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>AI-assisted development\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Code assistants, testing and code review, CI\u002FCD integration\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>2 – 5 days\u003C\u002Fp>\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Data and AI teams\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Developing in-house LLM applications\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>RAG, agent architectures, evaluation, MLOps\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>A few days – a few months\u003C\u002Fp>\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Security, legal and compliance\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Recognizing risks, establishing policy\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Model attack types, data leakage, regulations\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>1 – 3 days\u003C\u002Fp>\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003Cp>These durations are a general framework; they vary depending on starting level and the proportion of hands-on practice.\u003C\u002Fp>\u003Cp>As a content example, for business units the \u003Ca target=\"_blank\" href=\"https:\u002F\u002Facademyclub.co\u002Fegitimler\u002Furetken-yapay-zeka-araclari-ve-efektif-kullanimlari-egitimi\" rel=\"noopener noreferrer\">Generative AI Tools and Effective Use Training\u003C\u002Fa> and \u003Ca target=\"_blank\" href=\"https:\u002F\u002Facademyclub.co\u002Fegitimler\u002Fprompt-engineering-openai-egitimi\" rel=\"noopener noreferrer\">Prompt Engineering & OpenAI Training\u003C\u002Fa> curricula show the typical scope at this level. For data teams, \u003Ca target=\"_blank\" href=\"https:\u002F\u002Facademyclub.co\u002Fegitimler\u002Fadvanced-rag-kurumsal-llm-uygulamalari\" rel=\"noopener noreferrer\">Advanced RAG & Enterprise LLM Applications\u003C\u002Fa> and \u003Ca target=\"_blank\" href=\"https:\u002F\u002Facademyclub.co\u002Fegitimler\u002Fagentic-ai-mcp\" rel=\"noopener noreferrer\">Agentic AI & MCP\u003C\u002Fa> give an idea of what an advanced-level program consists of.\u003C\u002Fp>\u003Cp>Avoid mixed groups: if the same class includes both a business analyst who has never written code and a senior developer, the trainer will lose one of the two.\u003C\u002Fp>\u003Ch2>Should you prefer off-the-shelf training or a custom corporate program?\u003C\u002Fh2>\u003Cp>Ready-made content may be sufficient for awareness and basic tool usage; however, for training expected to change the way work is done, a custom, hands-on corporate program is more suitable.\u003C\u002Fp>\u003Ctable>\u003Ctbody>\u003Ctr>\u003Cth colspan=\"1\" rowspan=\"1\">\u003Cp>Criterion\u003C\u002Fp>\u003C\u002Fth>\u003Cth colspan=\"1\" rowspan=\"1\">\u003Cp>Asynchronous video training\u003C\u002Fp>\u003C\u002Fth>\u003Cth colspan=\"1\" rowspan=\"1\">\u003Cp>Open class\u003C\u002Fp>\u003C\u002Fth>\u003Cth colspan=\"1\" rowspan=\"1\">\u003Cp>Corporate-specific live training\u003C\u002Fp>\u003C\u002Fth>\u003Cth colspan=\"1\" rowspan=\"1\">\u003Cp>Hands-on program (training + project or competition)\u003C\u002Fp>\u003C\u002Fth>\u003C\u002Ftr>\u003Ctr>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Fit with the organization’s content\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Low\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Low – medium\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>High\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>High\u003C\u002Fp>\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Cost per person\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Low\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Medium\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Decreases as group grows\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Relatively high\u003C\u002Fp>\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Scalability\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Very high\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Low\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Medium\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Low – medium\u003C\u002Fp>\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Practice with corporate processes\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>None\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>None\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Possible\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>At the center of the program\u003C\u002Fp>\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Interaction with the trainer\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>None or limited\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Present\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>High\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>High, including mentorship\u003C\u002Fp>\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Suitable for\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Basic awareness for a broad audience\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Specialization for a few people\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>A team gaining shared competence\u003C\u002Fp>\u003C\u002Ftd>\u003Ctd colspan=\"1\" rowspan=\"1\">\u003Cp>Turning competence into concrete output\u003C\u002Fp>\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003Cp>For many organizations, the realistic solution is a combination of these options: a short asynchronous module for all employees, corporate-specific live training for selected teams, and then a small project period.\u003C\u002Fp>\u003Cp>Academy Club falls into the third and fourth columns of this table: it delivers live training whose content, duration, and group size are designed around the organization, and it organizes \u003Ca target=\"_blank\" href=\"https:\u002F\u002Facademyclub.co\u002Fyarismalar\" rel=\"noopener noreferrer\">technology competitions\u003C\u002Fa> such as hackathons, datathons, and ideathons. If you need to reach thousands of employees at once with a self-paced video library, asynchronous platforms respond more directly to that need.\u003C\u002Fp>\u003Ch2>How should a training provider and trainer be evaluated?\u003C\u002Fh2>\u003Cp>Evaluate the provider not by the size of its catalog but by whether the trainer has applied the subject in real projects, how up to date the content is, and how the program is adapted to your organization. AI tools change within a few months; an outdated curriculum may be describing methods that are already behind.\u003C\u002Fp>\u003Cp>Ask the following questions at the proposal stage:\u003C\u002Fp>\u003Cul>\u003Cli>\u003Cp>\u003Cstrong>Trainer:\u003C\u002Fstrong> Who will deliver the training, and on which projects have they worked on this subject?\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Currency:\u003C\u002Fstrong> When was the curriculum last updated, and which tool and model versions are covered?\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Adaptation:\u003C\u002Fstrong> How will the content be tailored to our sector and scenarios?\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Hands-on ratio:\u003C\u002Fstrong> How much of the time is lecture, and how much is hands-on practice by participants?\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Data and environment:\u003C\u002Fstrong> Which tools will be used for practice, and how will corporate data be protected if used?\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Assessment:\u003C\u002Fstrong> What kind of evaluation and report is provided at the end of the training?\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>References:\u003C\u002Fstrong> Are there publicly verifiable projects at a similar scale or in a similar sector?\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Cp>Training that turns into the promotion of a single product loses its value once your organization switches tools; training that teaches concepts and an evaluation habit is lasting.\u003C\u002Fp>\u003Ch2>How do data security and regulations affect the choice of training?\u003C\u002Fh2>\u003Cp>Data security and regulations are both a topic that should be included in the training content and a constraint that determines how the training is conducted. At every level, training is expected to cover at least the following:\u003C\u002Fp>\u003Cul>\u003Cli>\u003Cp>\u003Cstrong>Data classification:\u003C\u002Fstrong> Personal data, customer data, and trade secrets must not be entered into publicly available tools.\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Output verification:\u003C\u002Fstrong> The model may produce convincing but false output (hallucination), and responsibility lies with the user.\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Corporate policy:\u003C\u002Fstrong> Which tools are approved and for which tasks they can be used.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Cp>In Turkey, the processing of personal data falls under Law No. 6698 on the Protection of Personal Data (KVKK) (\u003Ca target=\"_blank\" href=\"https:\u002F\u002Fwww.kvkk.gov.tr\" rel=\"noopener noreferrer\">kvkk.gov.tr\u003C\u002Fa>). For organizations operating in the EU, Article 4 of the EU AI Act requires providers and deployers of AI systems to ensure a sufficient level of AI literacy among their staff; this provision has been in effect since February 2, 2025 (Source: \u003Ca target=\"_blank\" href=\"https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2024\u002F1689\u002Foj\" rel=\"noopener noreferrer\">Regulation (EU) 2024\u002F1689\u003C\u002Fa>, 2024).\u003C\u002Fp>\u003Cp>In regulated sectors, security may be a separate training topic. For example, the AI Security program Academy Club designed for Fibabanka employees covered model attack types, integrating generative AI tools into banking systems without causing data leakage, and the defensive use of AI (\u003Ca target=\"_blank\" href=\"https:\u002F\u002Facademyclub.co\u002Fhaberler\u002Ffibabanka-ai-security-egitimi\" rel=\"noopener noreferrer\">news\u003C\u002Fa>).\u003C\u002Fp>\u003Ch2>How is corporate AI training chosen step by step?\u003C\u002Fh2>\u003Cp>Corporate AI training is chosen in seven steps: defining the goal, grouping participants, measuring level, identifying use cases, comparing proposals, running a pilot, and setting up a measurement plan.\u003C\u002Fp>\u003Col>\u003Cli>\u003Cp>\u003Cstrong>Write the business goal.\u003C\u002Fstrong> State in a single sentence which task will be performed differently after the training.\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Group participants by role.\u003C\u002Fstrong> Treat management, business units, software, data, and security teams separately.\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Measure the current level.\u003C\u002Fstrong> Use a short survey or pretest to identify who is already using the tools.\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Select two or three use cases.\u003C\u002Fstrong> Build examples around your organization’s real workflows.\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Compare proposals using the same criteria.\u003C\u002Fstrong> Put trainer profile, adaptation level, hands-on ratio, data security, and assessment method into a table.\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Start with a pilot group.\u003C\u002Fstrong> Run the program with a single group first, then refine and expand based on feedback.\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Set up the measurement plan before the training.\u003C\u002Fstrong> Record the pre-training value of the metric you will track.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Fol>\u003Ch2>How is it measured whether the training worked?\u003C\u002Fh2>\u003Cp>The impact of the training is measured not by participant satisfaction but by the change in how work is done a few weeks after the training. The widely used Kirkpatrick model defines four levels (\u003Ca target=\"_blank\" href=\"https:\u002F\u002Fwww.kirkpatrickpartners.com\u002Fthe-kirkpatrick-model\u002F\" rel=\"noopener noreferrer\">Kirkpatrick Partners\u003C\u002Fa>):\u003C\u002Fp>\u003Cul>\u003Cli>\u003Cp>\u003Cstrong>Reaction:\u003C\u002Fstrong> How participants rated the training; a post-training survey.\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Learning:\u003C\u002Fstrong> Whether the skill was acquired; the difference between pretest and posttest, a practice task.\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Behavior:\u003C\u002Fstrong> Whether what was learned is being used at work; the active usage rate of approved tools.\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp>\u003Cstrong>Results:\u003C\u002Fstrong> Impact on business outcomes; completion time of a specific task, error or rework rate.\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Cp>For the last two levels, you need to know the pre-training value. Managers allowing their teams time and permission to use the tools after training also directly affects the outcome.\u003C\u002Fp>\u003Ch2>Observations from the field: Where do organizations struggle most with AI training?\u003C\u002Fh2>\u003Cp>Organizations struggle most often because they plan training as a one-time event and fail to build a bridge between training and daily work. The following observations are based on recurring situations Academy Club has encountered in corporate technical training and technology competitions.\u003C\u002Fp>\u003Cp>\u003Cstrong>Training comes before tool access.\u003C\u002Fstrong> Participants learn how to use an assistant but cannot use it the next day because they lack a license or access permission within the organization. The training date needs to be set according to when approved tools and usage policy are ready.\u003C\u002Fp>\u003Cp>\u003Cstrong>Generic examples are not memorable.\u003C\u002Fstrong> When participants work on their own reports, their own codebases, or their own anonymized customer requests, both engagement and post-training usage change.\u003C\u002Fp>\u003Cp>\u003Cstrong>In technical teams, the problem is habit, not knowledge.\u003C\u002Fstrong> Most developers have already tried code assistants; what is missing is consistently embedding the assistant into testing, code review, and documentation steps. The training conducted with Softtech engineers was also focused in this direction: running assistants from the terminal and integrating them into CI\u002FCD and daily development practices (\u003Ca target=\"_blank\" href=\"https:\u002F\u002Facademyclub.co\u002Fhaberler\u002Fsofttech-cli-ile-kod-asistanlari-calistirma-egitimi\" rel=\"noopener noreferrer\">news\u003C\u002Fa>).\u003C\u002Fp>\u003Cp>\u003Cstrong>In RAG projects, the real work is evaluation.\u003C\u002Fstrong> Data teams can build a prototype quickly, but without a test set to systematically measure answer accuracy, they cannot move it to production. In advanced training, time spent on evaluation and access permissions provides more benefit than time spent explaining the architecture.\u003C\u002Fp>\u003Cp>\u003Cstrong>Competition formats complete what training leaves incomplete.\u003C\u002Fstrong> In time-limited events such as hackathons or ideathons, teams test what they have learned against a real problem, and people from different departments work together.\u003C\u002Fp>\u003Ch2>Closing\u003C\u002Fh2>\u003Cp>The right corporate AI training starts from a clear business goal, separates participants by role, has them practice on the organization’s own scenarios, and measures results through change at work. Choosing a provider and tool becomes much easier once this framework is clear. If you would like to discuss a program tailored to your organization, you can fill out Academy Club’s \u003Ca target=\"_blank\" href=\"https:\u002F\u002Facademyclub.co\u002Fegitimler\u002Ftalep\" rel=\"noopener noreferrer\">training request form\u003C\u002Fa>.\u003C\u002Fp>","",[14,17,20,23,26],{"answer":15,"question":16},"Both work; what matters is the hands-on ratio and group size. The in-person format is advantageous for intensive workshops, while the online format is advantageous for bringing together teams from different cities and spreading the program over several weeks.","Should corporate AI training be delivered online or in person?",{"answer":18,"question":19},"No. Training aimed at business units is built around tool usage, prompt writing, and output verification. Coding knowledge becomes a prerequisite for technical topics such as LLM application development or RAG.","Is coding knowledge required for non-technical employees?",{"answer":21,"question":22},"The most practical approach is to deliver training using the tool your organization plans to use and that your security team has approved. If you have not yet chosen a tool, prefer content that teaches concepts independently of any specific tool, so the skill remains valid even if the tool changes.","Which AI tool should the training be based on?",{"answer":24,"question":25},"Pricing generally varies based on the level of content customization, the trainer’s expertise, duration, and group size; proposal-based pricing is common for custom corporate programs. Also include tool licenses, the time participants will be away from work, and follow-up sessions in your budget.","How should the training budget be planned?",{"answer":27,"question":28},"In the first few weeks, give participants small tasks to apply in their actual work and schedule a follow-up session. Using an internal channel where good examples are shared keeps engagement alive. Since tools change rapidly, the content also needs to be updated and repeated at regular intervals.","What should be done to make the training’s impact last?",[30,42,49,61,68],{"id":31,"title":32,"slug":33,"summary":34,"cover_image_url":35,"category":36,"duration_hours":41,"level":12,"module_count":40},28,"Generative AI Tools and Effective Usage Training","uretken-yapay-zeka-araclari-ve-efektif-kullanimlari-egitimi","With the introduction of generative AI tools such as ChatGPT, Claude, Gemini, and Midjourney into the business world, the way we work is being fundamentally transformed across many areas—from writing and code development to marketing content and data analysis. Companies are now saving time, reducing operational workload, and generating more creative solutions by leveraging these tools in report preparation, presentation design, customer communication, software development, and strategic decision-making processes. However, unlocking the true potential of these tools requires knowing proper prompt writing techniques and understanding the limitations of these tools as well as ethical usage principles.\n\nThe Generative AI Tools and Effective Usage Training equips participants with hands-on knowledge of how to integrate these technologies into their daily workflows, which tools to use in which scenarios, and prompt engineering techniques that maximize productivity. For corporate organizations, this training offers a concrete roadmap for increasing employee productivity, saving time on repetitive tasks, improving content quality, and making a safe, ethical, and strategic transition to AI-supported business processes.","https:\u002F\u002Facademyclub.b-cdn.net\u002Ftrainings\u002F4bbcce04dc1a497c990d02c8a35ae702.webp",{"id":4,"name":37,"slug":38,"icon":39,"order":40},"Artificial Intelligence","yapay-zeka","pi-sparkles",0,null,{"id":43,"title":44,"slug":45,"summary":46,"cover_image_url":47,"category":48,"duration_hours":41,"level":12,"module_count":40},29,"LLM Orchestration & Langchain Training","llm-orchestration-langchain-egitimi","Large Language Models (LLMs) have become central to enterprise software development today; however, a single LLM call is often insufficient to solve real-world problems on its own. From document-based question-answering systems to autonomous agents, from multi-step workflows to external API integrations, these scenarios require multiple models, tools, and data sources to work together in a coordinated manner. This is precisely where the LLM orchestration approach comes in, along with LangChain—the most widely used open-source framework in this field—which has become a critical layer enabling companies to move their AI projects from prototype to production.\n\nThis training aims to equip participants with the ability to build chains, agents, memory management, and RAG (Retrieval-Augmented Generation) architectures using the LangChain ecosystem. From the perspective of enterprise companies, this training paves the way for building a qualified technical team capable of developing fast, scalable, and cost-effective solutions across many domains—from customer service chatbots to internal documentation assistants, from process automation to data analytics agents—while also accelerating the process of turning AI investments into tangible business outcomes.","https:\u002F\u002Facademyclub.b-cdn.net\u002Ftrainings\u002Fdd672bb0a70c4eecb9781ec620360b0e.webp",{"id":4,"name":37,"slug":38,"icon":39,"order":40},{"id":50,"title":51,"slug":52,"summary":53,"cover_image_url":54,"category":55,"duration_hours":41,"level":12,"module_count":40},101,"Power BI, Business Intelligence Training","power-bi-is-zekasi-egitimi","Today, companies generate millions of rows of data every day; from sales figures to stock movements, from customer behavior to financial statements, this data means nothing unless it is analyzed properly. Microsoft Power BI has become one of the most widely preferred business intelligence platforms in the world, bringing scattered data sources together under a single roof and enabling interactive reports, dynamic dashboards, and real-time analyses. Going beyond Excel with capabilities such as DAX formulas, data cleaning with Power Query, and automated reporting, Power BI accelerates decision-making processes and sits at the heart of data-driven management, regardless of industry.\n\nThis training aims to equip participants with hands-on skills in data modeling, relationship building, creating calculated fields with DAX, and interactive visualization using Power BI Desktop and Power BI Service. By the end of the training, participants will be able to transform raw data into meaningful, manageable reports and automate repetitive manual Excel reporting processes. For corporate organizations, this training means shorter reporting times, consistent data across departments, and the ability for management to make decisions based on instant, accurate data—making it a strategic investment that directly boosts operational efficiency.","https:\u002F\u002Facademyclub.b-cdn.net\u002Ftrainings\u002Ff85bddbb25f14dbc82fb975378cf89e9.webp",{"id":56,"name":57,"slug":58,"icon":59,"order":60},5,"Data & Analytics","veri-analitik","pi-chart-bar",4,{"id":62,"title":63,"slug":64,"summary":65,"cover_image_url":66,"category":67,"duration_hours":41,"level":12,"module_count":40},125,"AI-Powered Software Development with Claude","claude-ile-yapay-zeka-destekli-yazilim-gelistirme","AI-powered coding tools are fundamentally transforming software development processes, dramatically increasing developer productivity. Claude, developed by Anthropic, is favored today by a wide range of users—from individual developers to large-scale software teams—thanks to its advanced code understanding, generation, and debugging capabilities; it is effectively used in critical areas such as code review, documentation generation, test writing, architectural design, and modernization of legacy systems. In an increasingly competitive software industry, teams equipped with the right tools can shorten development timelines while improving code quality and reducing technical debt.\n\nThis training aims to equip participants with hands-on examples of how to effectively use Claude at every stage of the software development lifecycle; participants will learn to get maximum value from Claude in code generation, refactoring, debugging, and documentation processes, gaining concrete skills they can integrate into their daily workflows. From a corporate perspective, this training enables software teams to increase development speed while improving code quality, resulting in shorter project delivery times, reduced operational costs, and the ability for technical teams to focus on more strategic work.","https:\u002F\u002Facademyclub.b-cdn.net\u002Ftrainings\u002F265adb70a49d44b2b3848fc6738eff41.webp",{"id":4,"name":37,"slug":38,"icon":39,"order":40},{"id":69,"title":70,"slug":71,"summary":72,"cover_image_url":73,"category":74,"duration_hours":41,"level":12,"module_count":40},93,"Fundamentals of Data Science Training","fundamentals-of-data-science-egitimi","Data science has become a strategic discipline that fundamentally transforms companies' decision-making processes today, converting raw data into meaningful insights and competitive advantage. From e-commerce to banking, from manufacturing to healthcare, statistical analysis, machine learning, and data visualization techniques are actively used to understand customer behavior, improve operational efficiency, anticipate risks, and optimize marketing strategies. Organizations capable of data-driven decision-making are now leaving intuition-based management approaches behind, enabling them to take faster, more accurate, and more sustainable steps in the market.\n\nThe Fundamentals of Data Science Training equips participants with the core building blocks of the data science discipline—data collection, cleaning, exploratory analysis, statistical inference, and fundamental machine learning concepts—through hands-on examples. By the end of this training, participants gain the ability to make sense of the data within their own departments, ask the right questions, and develop data-driven solution proposals. From a corporate perspective, this training strengthens cross-departmental data-driven collaboration by building a data-literate workforce, increases the speed and accuracy of decision-making processes, and paves the way for data science to become an embedded cultural competency within the organization.","https:\u002F\u002Facademyclub.b-cdn.net\u002Ftrainings\u002F65370543e2e1432ea8588e49b5470c89.webp",{"id":56,"name":57,"slug":58,"icon":59,"order":60},"2026-10-14T17:34:24.003307+03:00",1792015379994]