Diploma in Data Science for Research with Python and Jupyter Notebook
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This course is tailored for aspiring data scientists and researchers looking to master Python and Jupyter Notebook for advanced data analytics. Participants learn foundational and advanced techniques in data manipulation, visualization, and predictive modeling.
Data science is at the forefront of modern research, and Python, paired with Jupyter Notebook, offers unparalleled tools for data manipulation, visualization, and analysis. This course takes participants from the basics of Python programming to advanced data science workflows. The curriculum starts with an introduction to Python, focusing on data structures, loops, and functions. Participants then explore essential libraries such as Pandas for data manipulation, NumPy for numerical computing, and Matplotlib for data visualization. Intermediate modules delve into data cleaning, exploratory data analysis, and advanced visualization techniques. The course also introduces predictive modeling, covering linear regression, decision trees, and clustering algorithms. Jupyter Notebook is used throughout, ensuring a seamless and interactive coding experience. Practical exercises and case studies from domains such as healthcare, business, and environmental science help participants gain hands-on experience. Weekly quizzes and coding challenges reinforce the learning process, and the final capstone project involves solving a complex real-world problem using Python and Jupyter Notebook.
Basic understanding of programming concepts, Python installed on a computer, and access to datasets for practice.
Aspiring data scientists, researchers using data analytics in their work, and professionals transitioning into data-driven roles.
