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Fundamentals of Neuroscience, Part 1: The Electrical Properties of the Neuron
Organic Chemistry 1
Mountains 101
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Explore advanced ChatGPT prompting techniques, from freeform to structured formats. Learn scientific principles, master fundamentals, and acquire skills in chain-of-thought and skeleton prompts for optimal results with large language models.
Explore how generative AI revolutionizes data analytics, streamlining tasks, transforming workflows, and ensuring ethical practices. Gain practical insights and real-world applications for data professionals.
Comprehensive overview of recommender systems, covering types, models, performance metrics, and design considerations. Equips learners with knowledge to create and evaluate effective recommendation systems.
Learn to combine AI and BI for maximum business value. Discover how to identify and assess AI use cases, explore common applications in BI, and see a live demo of PDF text extraction using computer vision.
Learn to create interactive data apps using KNIME's low-code/no-code approach. Discover how to build, visualize, and deploy analytics solutions with user-friendly interfaces for end-users to gather insights effortlessly.
Explore text mining and NLP techniques using KNIME Analytics Platform. Learn sentiment analysis, topic extraction, and build a real-time tweet analysis app in this no-code tutorial.
Discover how to build scalable multi-agent AI systems using LangChain, exploring design patterns, orchestration techniques, and production-ready architectures beyond single agents.
Learn effective data visualization techniques to transform insights into impactful stories. Covers chart theory, Python coding with pandas and plotly, and practical tips for creating compelling, interactive visualizations.
Explore strategies to accelerate and automate AI/ML workflows using Kubernetes, leveraging open-source tools like Jupyter Notebooks and TensorFlow for efficient development and deployment.
Explore tokenization in NLP, from basics to advanced techniques. Learn about word embeddings, text splitting, BytePair Encoding, and token vectorization for enhanced language model performance.
Learn to develop and deploy an interactive machine learning app on Azure, covering UI creation, model development, and CI/CD configuration for seamless production deployment.
Learn best practices for unit testing data science code, including handling data inputs, model training, and evaluation. Gain insights on bridging software engineering and data science for more robust ML applications.
Explore AI and computer vision's role in enhancing road safety through real-time edge-based deep learning systems, addressing challenges and leveraging technological trends to reduce traffic fatalities.
Learn to create an interactive dashboard from raw data using Python. Master data cleaning, exploration, modeling, and visualization techniques for real-world data science projects.
Explore topological algorithms for time series comparison using persistent homology. Learn implementation in R, understand caveats, and gain practical insights through live coding and dataset analysis.
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