Machine learning is reshaping industries, but the growing demand for ML skills has exposed a critical talent gap. This whitepaper emphasizes the need for practical, project-based learning to bridge academic theory and real-world application. Employers seek professionals who understand model development, deployment, and maintenance—not just algorithms. Cloud-based tools, version control, data pipelines, and responsible AI practices are core competencies. Collaboration across data science, engineering, and business teams is also vital. Building these skills through hands-on experience accelerates career growth and ensures organizations can fully realize ML’s potential.

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