📅 2023-06-22 — Session: Designed Curriculum for Data Science and Big Data Courses
🕒 21:40–22:45
🏷️ Labels: Curriculum Design, Data Science, Big Data, Machine Learning, Ethics
📂 Project: Teaching
⭐ Priority: MEDIUM
Session Goal: The session aimed to design and outline the curriculum for various courses related to Data Science, Big Data, and their applications across different domains.
Key Activities:
- Developed a detailed structure for a course on Exploratory Data Analysis, covering data acquisition, cleaning, visualization, and analysis techniques.
- Outlined the curriculum for a Big Data course, focusing on concepts, technologies, and practices related to data processing, including Hadoop, Spark, and Apache Kafka.
- Created frameworks for courses on the application of data science in fields like astronomy, biology, health, and technology, emphasizing practical data processing and analysis techniques.
- Planned sessions on Machine Learning and Neural Networks, covering supervised and unsupervised learning, model evaluation, and neural network architecture.
- Addressed ethical considerations in data science, including biases, privacy, and responsible data handling.
- Compiled a comprehensive overview of a Data Mining course, detailing techniques and tools for data acquisition, organization, processing, and analysis.
Achievements:
- Successfully structured multiple course outlines, ensuring comprehensive coverage of theoretical and practical aspects.
- Integrated ethical considerations and best practices into the data science curriculum.
Pending Tasks:
- Finalize session-specific content and practical exercises for each course.
- Develop assessment criteria and evaluation methods for the courses.
- Collaborate with domain experts to refine course materials and ensure relevance.