Rigorous trainer selection
Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.
- Triple validation: technical, pedagogical, sectoral.
- Minimum rating 4.8/5 over the last 12 sessions.
Describe your need, get a tailored program and a pre-filled quote in 3 min. A 100% free call with an advisor.
Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.
Don't let this gap widen
Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.
Organizations that don't train their talents on key topics see their competitiveness drop.
Every quarter without training is a gap widening with competitors who invest.
The cost of inaction quickly exceeds that of well-targeted training.
Discover the advanced principles of supervised fine-tuning applied to software testing, by preparing labeled datasets from real source code and QA logs. Use PyTorch and Hugging Face Transformers to structure instruction-response pairs oriented towards unit tests, perform automated data cleaning, and validate quality via expert metrics like BLEU and ROUGE. Conclude with a practical exercise curating 500 examples for a first simulated fine-tuning, with real-time feedback to optimize your professional workflow.
Dive into optimized architectures for SFT with LoRA and QLoRA, tailored to expert unit test generation. Set up training sessions on cloud GPUs via Google Colab Pro, integrate specialized software testing prompts, and monitor convergence with Weights & Biases. Perform a complete fine-tuning on a base model like Mistral-7B, generate 100 unit tests for an open-source project, analyze results using coverage tools like pytest, and iterate on hyperparameters for over 90% precision.
Explore PEFT techniques for hybrid SFT integrating functional tests and quality assurance, using multi-modal datasets from Selenium and Cypress. Implement training loops with simulated human feedback via lightweight RLHF, deploy on Dockerized environments, and test robustness against edge cases in software QA. Produce a deliverable report with F1-score metrics > 0.95, exercises on automated mutation testing, and memory optimization for enterprise scaling.
Master the deployment of fine-tuned SFT models in CI/CD pipelines dedicated to software testing, using MLflow for tracking and Kubernetes for orchestration. Integrate your QA LLM into GitHub Actions, automate functional test generation post-commit, and set up A/B tests to validate speed gains. Complete an end-to-end project on an e-commerce repo, measure ROI via 40% reduction in testing time, and prepare REST APIs for seamless production integration.
Perfect SFT optimization for scalability in software QA using DistilBERT and TRL libraries, handling massive volumes of legacy code. Analyze real cases from Fortune 500 companies, implement knowledge distillation for lightweight models, and evaluate via custom benchmarks like HumanEval-QA. Finalize with a hackathon challenge: fine-tune a model for 1000+ unit/functional tests, produce a certifying portfolio, and plan a post-training roadmap for maximum ROI.
The Training Supervised Fine-Tuning (SFT) - Mastering AI Software Testing program is delivered onsite or remote (blended-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.
The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.
For the smooth delivery of the Training Supervised Fine-Tuning (SFT) - Mastering AI Software Testing program, the following equipment is required:
For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.
Assessment of skills acquired during the Training Supervised Fine-Tuning (SFT) - Mastering AI Software Testing program is performed through:
Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.
Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.
Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.
Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.
30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.
No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.
Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.
A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.
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JavaScript DevelopmentIndustry-certifiedAvailable on-site and remotely. Pick your city to see the local training center.
30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.