Course Content
Advanced Topics in AI and Data Science
Duraction: 27-32 Weeks
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Advanced data visualization using Tableau or Power BI
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Reinforcement learning and its applications in robotics and gaming
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Time series analysis and forecasting using Prophet and ARIMA models
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Natural Language Processing (NLP) and Text Analytics
Duration: 33-36 Weeks
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Text preprocessing and feature extraction
00:00
Building NLP models using libraries like NLTK and SpaCy
00:00
AI Ethics and Responsible AI
Duration: 37-41 Weeks
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Ethical considerations in AI and data science
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Responsible AI practices, bias detection, and mitigation
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Draft LessonRegulatory and legal aspects of AI and data science, including GDPR and data privacy laws
00:00
Industry-Driven Projects and Case Studies
Duration: 42-45 Weeks
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Application of AI and data science in specific industries, such as healthcare, finance, and e-commerce
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Industry-driven projects and case studies using real-world datasets
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Final assessment and project presentations aligned with industry job requirements
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Job Readiness and Soft Skills
Duration: 46-48 Weeks
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Resume building and crafting a compelling professional profile tailored for AI and data science roles
00:00
Interview preparation, including technical interviews and case study assessments commonly encountered in the industry.
00:00
Networking strategies and building a professional online presence to enhance job prospects.
00:00
Interactive sessions to address specific career goals and gain valuable advice for navigating the job market
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Capstone Project for Real-World Application
Duration: 49-52 Weeks
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Integrating all learned concepts into a comprehensive project
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Addressing real-world digital marketing and data analytics challenges
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Presentation of the capstone project to industry professionals
00:00
About Lesson

Reinforcement learning and its applications in robotics and gaming

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