"Implement Data Science & Machine Learning Solutions for AI in Microsoft Fabric" simplifies the entire process—from data prep to deployment. Learn to preprocess data with Data Wrangler, train models using MLflow, and automate predictions—all in one platform. Whether you're a data scientist or analyst, this 5.5-hour course offers actionable skills for real-world AI projects. Jumpstart your journey and turn raw data into actionable intelligence!
Start your journey today:
Module 1: Introduction to Microsoft Fabric (20 min)
Module 2: Data Science Fundamentals (46 min)
Module 3: Data Exploration with Notebooks (1 hr 27 min)
Module 4: Preprocessing with Data Wrangler (1 hr 10 min)
Module 5: Model Training & MLflow (54 min)
Module 6: Batch Predictions (50 min)
Learn to build, train, and deploy ML models in Microsoft Fabric. Master Data Wrangler, MLflow, and batch predictions.
Familiarity with basic data concepts and terminology.
Microsoft Certified: Azure AI Fundamentals (AI-900) is an entry-level certification designed to validate foundational knowledge of AI and machine learning concepts, including computer vision, natural language processing (NLP), generative AI, and responsible AI principles. Ideal for both technical and non-technical professionals, it requires no prior coding experience and offers free, flexible learning resources via Microsoft Learn. The certification enhances career prospects in high-demand roles like AI Engineer or Data Scientist, with potential salary increases up to 20%, while serving as a gateway to advanced Azure certifications (e.g., AI-102). Cost-effective and time-efficient (preparation in 10–30 hours), the exam focuses on real-world applications using Azure Cognitive Services, OpenAI APIs, and Azure Machine Learning. With permanent validity and global recognition across 90+ countries, it equips professionals to drive AI innovation in industries such as healthcare and finance. Start your AI journey with Microsoft Learn today!
SPOTO's study resources provide comprehensive coverage of the exam syllabus, aligning with key topics like ML problem framing, data processing, model optimization, and pipeline automation. The materials include structured learning paths, practice exams, and real-world case studies that mirror the certification's focus on designing, implementing, and deploying machine learning solutions with Microsoft services and ML workflows. By leveraging SPOTO's targeted content, candidates can efficiently bridge knowledge gaps, reinforce practical skills, and gain familiarity with the exam format. This focused preparation increases confidence and readiness, particularly for complex tasks such as deploying CI/CD pipelines or optimizing model performance—areas emphasized in the certification. Combined with hands-on experience, SPOTO's resources offer a strategic advantage for achieving certification success.
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