This course provides a comprehensive introduction to the essential software tools used in data science, focusing on Python, R, and SQL. The curriculum is designed for novice programmers and covers fundamental concepts, programming techniques, and practical applications in data science. Emphasis will be placed on self-discovery of solutions.
1.1 Introduction to Python and its applications in data science. , 1.2 Python installation and setup, including GIT and source code editors , 1.3 Basic syntax, variables, and data types. , 1.4 Control structures: if statements, loops , 1.5 Lists, tuples, dictionaries, and sets. , 1.6 Functions: definition, arguments, return values. , 1.7 Reading from and writing to files. , 1.8 Handling exceptions and errors. , 1.9 Working with different file formats CSV, JSON. , 1.10 Python packages, 1.11 Introduction to NumPy: arrays, basic operations. , 1.12 Introduction to Pandas: Series and DataFrames. , 1.13 Data manipulation with Pandas. , 1.14 Introduction to data visualisation. , 1.15 Plotting with Matplotlib: line plots, bar charts, histograms. , 1.16 Advanced visualisation with Seaborn.
2.1 Introduction to R and its applications in data science. , 2.2 R installation and setup. , 2.3 Basic syntax, variables, and data types. , 2.4 Control structures: if statements, loops. , 2.5 Vectors, lists, matrices, data frames. , 2.6 Functions: definition, arguments, return values. , 2.7 Data manipulation with dplyr. , 2.8 Introduction to data visualisation in R. , 2.9 Plotting with ggplot2: basic plots, aesthetics, and themes. , 2.10 Advanced visualisation techniques.
3.1 Introduction to databases and SQL. , 3.2 Basic SQL commands: SELECT, INSERT, UPDATE, DELETE. , 3.3 Filtering, sorting, and grouping data. , 3.4 Advanced SQL concepts: joins, subqueries, indexes. , 3.5 Using SQL with Python SQLite and SQLAlchemy. , 3.6 Using SQL with R DBI and RSQLite.
4. Project (4.1 Group project integrating Python, R, and SQL for data analysis.)
By the end of the course, students should be able to do the following:
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SCQF Level: 11
Credits: 15