Hands On Training for Data Science
This program introduces students and professionals to the field of data science through a hybrid model of self-paced online modules and immersive hands-on training. Topics include Python programming, data visualization, machine learning, data ethics, and real-world case studies. Participants gain essential technical skills, industry insights, and exposure to practical applications in sectors such as agriculture, wind energy, water resource and other types of renewable energy.
Skills / Knowledge
- Data Analysis
- Python Programming
- Machine Learning Fundamentals
- Data Visualization
- Ethics in Data Science
- Technical Readiness
- AI
- Big Data
Earning Criteria
Optional
By the end of the program, learners will be able to demonstrate basic proficiency in Python programming for data exploration, clean and preprocess datasets using standard tools, visualize data effectively with key libraries, apply exploratory data analysis techniques, describe core machine learning concepts, and evaluate ethical implications related to AI and Big Data.
Learners will be assessed through completion of online exercises, active participation during the in-person sessions, and a final case study project. Assessment will focus on the learner’s ability to apply data science concepts accurately and effectively, communicate insights clearly, and demonstrate a solid understanding of ethical considerations.
Participants will begin with online modules that introduce the fundamental concepts of data science, including Python programming, data cleaning, data visualization, and machine learning. These self-paced sessions ensure foundational knowledge and technical readiness. The experience culminates in a two-day, in-person hands-on training session where learners apply their knowledge to practical case studies, such as solving real-world challenges in agriculture or renewable energy. This combination of theory and application equips participants with the skills necessary to meet industry expectations.