Cerdas Inovasi Digital

Python Portfolio for Theses and Dissertations

1,000 analysis projects in Python, from regression and clustering to optimisation and data quality, spread over 25 fields of study and three levels: undergraduate thesis, master's thesis and doctoral dissertation. Each page shows a result sheet from synthetic data, the method, the variables, example code and three price packages.

Prices start from US$16, with three packages to choose from for every project.

Consult or order via WhatsApp

1,000 of 1,000 projects

How an order works

1ConsultYou share your research question, data format and level (thesis, master or doctoral), and we agree on the scope.
2QuoteWe confirm the method, the package and the price based on how demanding the analysis is.
3Build and reviewYou review the first results within days and can request revisions.
4HandoverWe deliver the code, figures and notes, and walk you through them so you can explain them yourself.

Result sheets use illustrative synthetic data. Python is a trademark of the Python Software Foundation.

Memuat

Python Portfolio for Theses and Dissertations

Mapping employees by work productivity and absence rate via K-Means with PCA Visualisation

Classifying customer repurchase decisions from satisfaction and visit frequency with Logistic Regression

Linear Discriminant Analysis to Distinguish Reef Fish Species from Body Morphometric Measurements

Applying Outlier Detection (IQR and Isolation Forest) to IoT device sensor data

Particle Swarm Optimization to Maximise student fitness achievement Based on lesson duration and weekly training frequency

Segmenting districts by immunisation coverage and poverty rate Using Hierarchical Clustering

Forecasting monthly rainfall of a city in Java Using Moving Average and Smoothing

Predicting child stunting status from maternal height and household income Using Decision Tree

Scenario Analysis of parameters of a simple weather forecast model Through Linear Programming

Principal Component Analysis of an Environmental Vulnerability Index from Land Cover and Population Density

Dimensionality Reduction of regional competitiveness indicators from capital spending and investment with Principal Component Analysis (PCA)

Classifying landslide susceptibility of land units Using Logistic Regression

Analysing differences in audit fees across audit firm sizes adjusted for client assets Using One-Way ANOVA

Statistical Comparison of differences in user satisfaction across interface versions Through Chi-Square Test

k-Nearest Neighbors to Classify Daily Air Quality Status from PM10 and Ozone Concentrations

Logistic Regression to Predict selection status in student swimming clubs Based on arm span and stroke rate

Testing differences in audit fees across audit firm sizes adjusted for client assets with t-test and Welch's Test

PCA to Summarise Household Diet Quality from Vegetable and Fruit Consumption Frequency

Segmenting provinces by economic growth and unemployment rate Using Hierarchical Clustering

Modelling dengue cases per district from rainfall and population density with Multiple Linear Regression

Linear Programming to Allocate a Scholarship Budget for Maximum Number of Recipients

Modelling online retail sales volume from advertising budget and discounts with Multiple Linear Regression

Finding Optimal Solutions for the promotion budget mix across digital and outdoor media Using Genetic Algorithm

Principal Component Analysis Summarising article length and number of images as article reading time Indicators

How an order works

Python Portfolio for Theses and Dissertations

Mapping employees by work productivity and absence rate via K-Means with PCA Visualisation

Classifying customer repurchase decisions from satisfaction and visit frequency with Logistic Regression

Linear Discriminant Analysis to Distinguish Reef Fish Species from Body Morphometric Measurements

Applying Outlier Detection (IQR and Isolation Forest) to IoT device sensor data

Particle Swarm Optimization to Maximise student fitness achievement Based on lesson duration and weekly training frequency

Segmenting districts by immunisation coverage and poverty rate Using Hierarchical Clustering

Forecasting monthly rainfall of a city in Java Using Moving Average and Smoothing

Predicting child stunting status from maternal height and household income Using Decision Tree

Scenario Analysis of parameters of a simple weather forecast model Through Linear Programming

Principal Component Analysis of an Environmental Vulnerability Index from Land Cover and Population Density

Dimensionality Reduction of regional competitiveness indicators from capital spending and investment with Principal Component Analysis (PCA)

Classifying landslide susceptibility of land units Using Logistic Regression

Analysing differences in audit fees across audit firm sizes adjusted for client assets Using One-Way ANOVA

Statistical Comparison of differences in user satisfaction across interface versions Through Chi-Square Test

k-Nearest Neighbors to Classify Daily Air Quality Status from PM10 and Ozone Concentrations

Logistic Regression to Predict selection status in student swimming clubs Based on arm span and stroke rate

Testing differences in audit fees across audit firm sizes adjusted for client assets with t-test and Welch's Test

PCA to Summarise Household Diet Quality from Vegetable and Fruit Consumption Frequency

Segmenting provinces by economic growth and unemployment rate Using Hierarchical Clustering

Modelling dengue cases per district from rainfall and population density with Multiple Linear Regression

Linear Programming to Allocate a Scholarship Budget for Maximum Number of Recipients

Modelling online retail sales volume from advertising budget and discounts with Multiple Linear Regression

Finding Optimal Solutions for the promotion budget mix across digital and outdoor media Using Genetic Algorithm

Principal Component Analysis Summarising article length and number of images as article reading time Indicators

How an order works