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Course Outline:


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.
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