Coming soon
Advanced Programming for Python
Course Objectives: In this course, students will learn 1. Different python libraries and their functionalities 2. To create database and access data using MySQL and SQLite 3. To design machine learning model in python Course Outcomes (COs): Course Course outcome (at course level) Learning and teaching strategies Assessment Strategies Paper Code- Paper Title - CLO 105. Categorize basic libraries of python with their utility in different business problems. CLO 106. Build data frame, import data set and perform pre-processing, descriptive and predictive analysis on business datasets. CLO 107. Communicate results by designing charts and plots like bar chart, line charts and ROC curve using python libraries. CLO 108. Create MySQL database and access data through MySQL queries for business domain. CLO 109. Design model based on advance machine learning algorithms using python libraries for business problems like retail management, Customer relationship management etc. CLO 110. Evaluate the performance of machine learning models. Approach in teaching: Interactive Lectures, Group Discussion, Tutorials, Case Study, Demonstrate Learning activities for the students: Self-learning assignments, presentations, Python exercises Class test, Semester end examinations, Quiz, Practical Assignments, Presentation, Peer Review
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
Importing pandas library, Usingseries and Data Frames, indexing, Grouping, aggregating, MergingdataFrames, dealing with missing values using dropna method ,filtering or filling in missing data, creating dataframes from dictionaries or nested dictionaries, accessing and changing values of data frame using loc,at,replace methods,reading and writing csv,excel files
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 seaborn library:Style functions, color palettes, Distribution plots ,categorical plots.
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)
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
