Advanced Programming for Python

Paper Code: 
MBB 322
Credits: 
4
Contact Hours: 
90.00
Max. Marks: 
100.00
Objective: 

Course Outcomes (COs):

       Courseoutcomes

Learning andteaching

strategies

AssessmentStrategies

On completion of this course, the students will be able to;

CO 114.Categorize basic libraries of python with their utility in different business problems.

CO 115.Build data frame, import data set and perform pre-processing, descriptive and predictive analysis on business datasets.

CO 116.Communicate results by designing charts and plots like bar chart, line charts and ROC curve using python libraries.

CO 117.Create MySQL database and access data through MySQL queries for business domain.

CO 118.Design model based on advance machine learning algorithms using python libraries for business problems like retail management, Customer relationship management etc.

CO 119.Evaluate the performance of machine learning models.

Approach inteaching:

 

Interactive Lectures,Group Discussion,Tutorials,CaseStudy

Classtest,Semesterend examinations,Quiz, Assignments,Presentation

 

18.00

Importing numpy library, creating numpy arrays, indexing and slicing arrays,performing numerical operations on arrays, converting data frames to numpy arrays, creating multidimensional arrays, numpy data type object (dtype), concatenating, reshaping and flattening multidimesional arrays, repeating patterns uisng “tile” method. Reading and writing data files using functions: savetxt, loadtxt, tofile ,fromfile,save ,load, genfromtxt

 

18.00

Importing pandas library, Usingseries and Data Frames, indexing, Grouping, aggregating, MergingdataFrames, dealing with missing values using dropnamethod ,filtering or filling in missing data, creating dataframes from dictionaries or nested dictionaries, accessing and changing values of data frame using loc,at,replacemethods,reading and writing csv,excel files

 

18.00

Importing Visualisation libraries: Matplotlib: format parameter of pylpot.plot ,subplots method, checking and defining ranges of axes, using linspace and linstyle, specifying legend, title Style, creating Scatter plots ,Bar charts, histogram, Stack charts, Saving plots. Importing seabornlibrary:Style functions, color palettes, Distribution plots ,categorical plots

 

18.00

Creating databases using MYSQL and SQLite: Importing the modules, creating connection object, creating tables, performing database operations (insert, update, delete),closing connection. .GUI programming with Tkinter: widgets(label, text, radio button, check boxes, entry, canvas, dialogs, menus)                  

18.00

Implementing Machine Learning with scikit-learn: loading and Visualizing datasets(sample sklearn datasets),splitting train and test data. Implementing deep learning with tensorflow and keras                                                                  

*Case studies related to entire topics are to be taught.

 

Essential Readings: 
  • Paul Gries, Jennifer Campbell and Jason Montojo, “Practical Programming: An Introduction to Computer Science using Python 3”, Second edition, Pragmatic Programmers,LLC,2013.
  • Robert Sedgewick, Kevin Wayne, Robert Dondero, “Introduction to Programming in Python: An Inter-disciplinary Approach, Pearson India Education Services Pvt. Ltd., 2016.
  • Timothy A. Budd, “Exploring Python”, Mc-Graw Hill Education (India) Private Ltd.,2015.

 

References: 

Suggested readings

•Timothy A. Budd, “Exploring Python”, Mc-Graw Hill Education (India) Private Ltd.,2015.

E resources

Journals

 

 

Academic Year: