Machine Learning with Python
Objective
The objective of this course is to work on industry-specific case studies and projects that reflect real-world challenges and solutions. Master advanced Python techniques and libraries for data manipulation, analysis, and visualisation tailored to industry needs. Gain proficiency in using libraries and frameworks like Scikit-learn, PyTorch etc. for scalable and efficient data processing. Develop, train, and fine-tune machine learning models focusing on practical performance metrics relevant to industry scenarios. Gain experience deploying models into production environments and integrating them with existing systems or applications. It provides the skills necessary to apply machine learning solutions effectively within a business context, address real-world problems, and drive value through data-driven decision-making.
Target Audience
Students who have done Bachelor of Technology (CS/IT), Bachelor of Computer Applications (BCA), Bachelor of Science in Information and Technology (B.Sc IT), Master of Computer Applications (MCA), Master of Science in Computer Science (M.Sc CS), Master of Science in Information and Technology (M.Sc IT) and professionals seeking a future in IT Industry.
Duration of Course
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Credit Weight
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Certificate
The participants will be provided with a certificate upon successful completion of the course.
Career Advancement
Many top companies and startups, including Google, Netflix, Amazon, and Tesla, rely on Python for developing machine learning and AI models. This makes learning machine learning with Python highly valuable for career growth. Python’s versatility and ability to scale from simple models to complex production systems make it a go-to language for real-world applications. Starting as a Machine Learning Engineer or Data Scientist, professionals can progress to senior roles such as Lead AI Engineer, and Data Science Manager. Industries Hiring Machine Learning with Python Professionals: Finance, Healthcare, Retail and E-commerce, Technology, Telecommunications, Manufacturing etc.
