Data science & AI
Data Science & AI involves extracting insights from data using statistical methods, machine learning, and AI algorithms. It enables automation, predictive analy...
Course Overview
Data Science & AI Course
This course provides a comprehensive introduction to Data Science and Artificial Intelligence (AI), covering key concepts, tools, and techniques used in real-world applications. You will learn how to collect, clean, and analyze data using Python, machine learning algorithms, and AI models.
The course covers:
✅ Data Science Foundations – Data preprocessing, visualization, and statistical analysis.
✅ Machine Learning – Supervised and unsupervised learning, model evaluation, and optimization.
✅ Deep Learning & AI – Neural networks, natural language processing (NLP), and computer vision.
✅ Hands-on Projects – Real-world applications in business, healthcare, and finance.
By the end of this course, you will have the skills to work on AI-driven projects, build predictive models, and apply AI solutions to real-world problems. Whether you're a beginner or an aspiring data scientist, this course will equip you with the knowledge to excel in the field.
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Course curriculum
Requirment
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1. Must have a reliable high-speed Internet connection
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2. Must possess a computer (laptop or desktop) that meets minimum technical specs
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3. Must use an up-to-date web browser
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4. Must have a quiet, dedicated study space
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5. Must have a functioning webcam and microphone
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6. Must maintain regular power supply and backup options (e.g., charger, UPS)
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7. Must be comfortable using email and online communication platforms
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8. Must have basic digital literacy (e.g., navigating websites, using word processors)
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9. Must demonstrate commitment to regular attendance (virtual or in-person)
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10. Must have time-management skills and a proactive study routine
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11. Must be prepared to participate in online surveys and feedback sessions
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12. Must ensure all required digital platforms (LMS, cloud storage, etc.) are accessible
Outcomes
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Students will consistently access and engage with online course content, virtual lectures, and collaboration tools.
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Students will efficiently run required online platforms and digital learning tools to complete assignments and projects.
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Students will seamlessly access digital resources and maintain uninterrupted participation in online discussions and activities.
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Students will concentrate on coursework, participate actively in virtual sessions, and complete assignments on time.
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Students will actively participate in synchronous virtual meetings and collaborative group discussions.
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Students will avoid disruptions during online classes, ensuring consistent engagement and timely submission of work.
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Students will receive, respond to, and utilize digital communications for course updates, collaborative projects, and feedback.
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Students will effectively use the course’s digital tools to access readings, complete assignments, and collaborate with peers.
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Students will participate in all scheduled sessions and actively engage in discussions, supporting their learning and group projects.
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Students will meet assignment deadlines, complete projects on schedule, and self-regulate their learning progress throughout the course.
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Students will contribute valuable input to improve course delivery and demonstrate reflection on their learning experiences.
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Students will seamlessly access all learning resources and submit assignments without technical delays.
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