Course Outline:
DURATION: 5 Days
Module 1: Introduction to Python:
- Define Python.
- Overview of Python.
- Understand why Python is Popular.
- Setup Python Environment.
- Understand Operands and Expressions.
- The Companies using Python.
- Different Applications where Python is Used.
- Discuss Python Scripts on UNIX/Windows.
- Values, Types, Variables.
- Operands and Expressions.
- Conditional Statements.
- Loops.
- Command Line Arguments.
- Writing to the Screen.
- Write your First Python Program.
- Understand Command Line Parameters and Flow Control.
Module 2: Sequences and File Operations:
- Python files I/O Functions.
- Numbers.
- Strings and related operations.
- Tuple – properties, related operations, compared with list.
- List – properties, related operations.
- Dictionary – properties, related operations.
- Set – properties, related operations.
Module 3: Deep Dive – Functions, OOPs, Modules, Errors and Exceptions:
- Understand Python Standard Libraries.
- Packages and Module – Modules, Import Options, sys Path.
- Functions – Syntax, Arguments, Keyword Arguments, Return Values.
- Function Parameters.
- Global Variables.
- Variable Scope and Returning Values.
- Lambda – Features, Syntax, Options, Compared with the Functions.
- Sorting – Sequences, Dictionaries, Limitations of Sorting.
- Errors and Exceptions – Types of Issues, Remediation.
- Object Oriented Concepts.
- Modules Used in Python.
- The Import Statements.
- Module Search Path.
- Package Installation Ways.
- Errors and Exception Handling.
- Handling Multiple Exceptions.
Module 4: Introduction to NumPy, Pandas and Matplotlib:
- Create arrays using NumPy.
- Perform various operations on arrays and manipulate them.
- Indexing slicing and iterating.
- Read & write data from text/CSV files into arrays and vice-versa.
- Create Series and Data Frames in Pandas.
- Data structures & index operations in pandas.
- Importing and exporting data.
- Indexing and slicing of data structures in pandas.
- Reading and Writing data from Excel/CSV formats into Pandas.
- Create simple plots in matplotlib.
- Grids, axes, plots, Markers, colours, fonts and styling.
- Types of plots – bar graphs, pie charts, histograms, Contour plots.
- Choose the right plot format for a problem at hand judiciously.
- Scale and add style to your plots.
Module 5: Data Manipulation:
- Basic Functionalities of a data object.
- Merging of Data objects.
- Concatenation of data objects.
- Types of Joins on data objects.
- Exploring a Dataset.
- Analysing a dataset.
