About This Course
In today's fast-paced business world, understanding AI is no longer optional -changer. The main driver behind? Data science is an exciting and full-of-opportunities emerging field. It covers economics, financial sectors, law, healthcare, public administration, social media, manufacturing, banking and financial institutions, etc. All industries are going to rely on quality data to make informed business decisions. This program provides participants with complete training, with theories, and hands-on practicals, using real-world use cases from various industries.
Learning Objectives
By the end of the course, participants will be able to:
- on experience with tools and techniques like programming, machine learning, and data analysis, enabling you to apply these skills directly to real-world business challenges and build a robust portfolio.
- Access to expert guidance and community: you'll learn from seasoned professionals and connect with a supportive community of peers, providing ongoing mentorship and networking opportunities to accelerate your career.
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Career-Ready Portfolio and Opportunities: Through practical projects and a structured curriculum, you'll develop an interactive portfolio based on real-world cases, positioning you to stand out to recruiters and transition into high-demand data science roles.
Prerequisites
- Familiarity with general IT concepts
- Basic technical background
- Willing to learn and engage with new ideas
Target Audience
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Training Outline
- Introduction to Data Science Workflow
- Mastering OSEMN Framework
- AI Tools for Data analytics
- Exploratory Data Analytics (EDA)
- Develop Machine Learning Models
- Q&A and Open Discussion
- Day 1 Recap
- Using Large Language Models (LLMs)
- Unsupervised Learning
- Develop Machine Learning Models
- Handling Unstructured Data
- Q&A and Open Discussion
- Day 2 Recap
- Group Consultation & Strategy Session
- Project Presentation
- Final Q&A and Closing Remarks