Data Science Using Python
(i) Python Language, Structures, Programming Constructs
Review of Python Language, Data types, variables, assignments, immutable variables,
Strings, String Methods, Functions and Printing, Lists and its operations, Tuples and
Dictionaries programs, Slicing strings,lists, tuples.
(ii) Data Science and Analytics Concepts
What is Data Science and Analytics? The Data Science Process, Framing the problem,
Collecting, Processing, Cleaning and Munging Data, Exploratory Data Analysis,
(iii)Introduction to NumPy Library
Numpy : Array Processing Package, Array types, Array slicing, Computation on NumPy
Arrays Ã¢â‚¬â€œ Universal functions ,Aggregations: Min, Max, etc., N-Dimensional arrays,
Broadcasting, Fancy indexing, sorting arrays, loading data in Numpy from various
(iv) Data Analysis Tool : Pandas
Introduction to the Data Analysis Library Pandas, Pandas objects Ã¢â‚¬â€œ Series and Data
frames, Data indexing and selection, Nan objects, Manipulating Data Frames,
Grouping, filtering, Slicing, Sorting, Ufunc, Combining Datasets- Merge and join.
Query Data Frame structures for cleaning and processing, lambdas. Aggregation
functions and applying user defined functions for manipulations.
(iv) Statistical Concepts and Functions
Statistics module, manipulating statistical data, calculating results of statistical
operations. Python Probability Distribution, Functions like mean, median, mode and
standard deviation. Concept of Correlation and Regression.
Visualization with Matplotlib, Simple line plots, scatter plots, Density and Contour
plots Ã¢â‚¬â€œ visualizing functions, Multiple subplots, Plotting histograms, bar charts, scatter
graphs and line graphs.
(vi) GUI Ã¢â‚¬â€œ Tkinter
Tk as Inbuilt Python module creating GUI applications in Python. Creating various
widgets like button, canvas, label, entry, frame, check button, label etc. Geometry
Management: pack, grid, place, organizing layouts and widgets, binding functions,
mouse clicking events. Building the complete interface of a project.
(vii) Machine Learning : The Next Step
What is Machine Learning? Types of Machine Learning Algorithms, Training the data
and Introduction to Various Learning Algorithms. Applications of Machine Learning.