What Is Programming? And How To Get Started
January 28, 2025
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Recommended experience
Beginner level
Basic knowledge of python programming language, probability and statistics. Working with analyzing data to extract knowledge.
Recommended experience
Beginner level
Basic knowledge of python programming language, probability and statistics. Working with analyzing data to extract knowledge.
Describe types of smart city-generated datasets, data mining techniques, and how to implement them using Python 3.
Explain how to read and preprocess data for data mining.
Apply data mining techniques to smart city-generated data and visualize and interpret the physical implications of the results.
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Internet of things (IoT) has become a significant component of urban life, giving rise to “smart cities.” These smart cities aim to transform present-day urban conglomerates into citizen-friendly and environmentally sustainable living spaces. The digital infrastructure of smart cities generates a huge amount of data that could help us better understand operations and other significant aspects of city life.
In this course, you will become aware of various data mining and machine learning techniques and the various dataset on which they can be applied. You will learn how to implement data mining in Python and interpret the results to extract actionable knowledge. The course includes hands-on experiments using various real-life datasets to enable you to experiment on your domain-related novel datasets. You will use Python 3 programming language to read and preprocess the data and then implement various data mining tasks on the cleaned data to obtain desired results. Subsequently, you will visualize the results for the most efficient description.
This module provides an overview of the course content and structure. In this module, you will learn about the different course elements. In this module, you will get acquainted with your instructor and get an opportunity to introduce yourself and interact with your peers.
2 videos1 reading1 discussion prompt
In this module, you will learn about data mining, why we need it, and the approach. The module also presents the basics of probability and statistics, which form the foundation for data mining. You will also gain insight into data preprocessing and data mining task identification.
12 videos4 readings2 assignments1 discussion prompt
In this module, you will learn about Python programming for data mining. The module also discusses important Python modules: NumPy , SciPy, and Matplotlib. You will learn to install Python using Anaconda and use the Jupyter notebook to write your code. The module also presents some examples demonstrating data preprocessing using Python.
6 videos4 readings2 assignments3 ungraded labs
In this module, you will learn about supervised learning (learning from examples). The module discusses two supervised learning tasks: regression and classification. You will also gain insights into several classification algorithms such as Bayesian classifiers, decision trees, support vector machines (SVM), and ensemble classifiers.
12 videos5 readings2 assignments1 discussion prompt9 ungraded labs
In this module, you will learn about unsupervised learning (learning from unlabelled data without any ground truth labels). The module also discusses frequent itemset mining. You will also gain an insight into several data clustering algorithms such as distribution-based, partitional, and hierarchical clustering.
11 videos5 readings2 assignments1 discussion prompt7 ungraded labs
In this module, you will learn about anomaly detection problems and algorithms. You will gain insight into anomaly detection techniques. You will learn to validate your results. When applying data mining to smart city data, you will also learn to avoid false discoveries using statistical significance testing and hypothesis testing.
5 videos2 readings2 assignments4 ungraded labs
In this module, you will learn about some advanced data mining algorithms such as artificial neural networks (ANN) and deep learning. You will develop an understanding of the applications of these algorithms. The module also analyzes hidden Markov models (HMMs) for modeling time series (sequential) data.
10 videos3 readings1 assignment1 discussion prompt4 ungraded labs
In this module, you are provided with your term-end project, instructions to complete the project, and the criteria for how your instructor will grade your submission.
1 video2 readings1 assignment1 ungraded lab1 plugin
Indian Institute of Technology Roorkee is among the foremost of institutes of national importance in higher technological education and in engineering, basic and applied research. More than 170 years old, IIT Roorkee ranks amongst the best technological institutions in the world and has contributed to all sectors of technological development. It has also been considered a trend-setter in the area of education and research in the field of science, technology, and business.
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