Website: Udemy
Mastering Python and R for Scientific Data Analysis
Master programming fundamentals: Learn core programming concepts such as variables, data types, control flow, functions, and modules in both Python and R.
Wrangle and analyze data: Effectively manage and manipulate your scientific data using file handling techniques in Python and data manipulation methods in R.
Perform statistical analysis: Utilize libraries like NumPy and SciPy in Python, along with core R functionalities, to conduct essential statistical analyses
Create informative visualizations: Craft compelling graphs and plots to communicate your research findings clearly using libraries like Matplotlib in Python
Explore Artificial Intelligence applications: Gain an introduction to AI, including deep learning techniques and their application to scientific research
Apply your skills to real-world problems: Put your newfound knowledge into practice by working through case studies that address various research scenarios