Телеграм канал «RESEARCH RESULT. THEORETICAL AND APPLIED LINGUISTICS»

🧠 Want to Add Data Science to Your Linguistic Toolkit? As linguistics becomes increasingly data-driven, skills in Python, data analysis, and machine learning are more valuable than ever. A fantastic (and free!) resource to get started is Kaggle Learn. What is it? Kaggle Learn offers bite-sized, hands-on courses in data science and programming. You can learn by doing, right in your browser. Why is this relevant for linguists? These skills can directly empower your research in areas like: 📊 Corpus Linguistics & NLP: Analyze large text datasets with Python (Pandas). 🤖 Computational Linguistics: Build models for text classification, sentiment analysis, and more with Machine Learning. 📈 Data Visualization: Create clear, powerful graphs and charts to present your findings (Seaborn, Matplotlib). 🔤 Phonetics & Acoustic Analysis:Process and analyze audio data. Perfect for beginners, the courses guide you from "Hello World" to building your first models. It's a practical way to bridge the gap between theoretical linguistics and modern computational methods. 💡 Start learning today: Kaggle Micro-Courses

🤖 AI in Academic Work and not Only: A Useful Resource Perplexity has released an extensive 40-page guide on integrating AI into workflows. While written for a broad audience, its core principles are perfectly suited for the tasks of researchers and educators. Why is this useful for academics? The guide is packed with practical advice and prompts that can be adapted for: Automating routine tasks: Helping draft administrative emails, course plans, and abstract summaries. Text and data analysis: Aiding in the initial processing of corpora, generating ideas for papers, and structuring thoughts. Scientific communication: Assisting in simplifying complex explanations or creating presentation content. Key Takeaways: Specificity & Context: Give your AI assistant clear goals and extensive background information for accurate results. Removing Yourself from the Loop: Delegate repetitive tasks to AI to free up your focus for deep analysis and hypothesis generation. Tool Synergy: Leverage the strengths of different AI assistants for a more powerful, combined approach. This guide is a great starting point for learning to use AI in a conscious and effective way. 📖 Read the guide here: pplx-at-work.pdf