data visualization with python peer graded assignment airline

Murat Kocak

Murat koçak, data science and analytics portfolio.

This Portfolio is a compilation of the Data Science and Analytics projects I have done for learning. It also contains my core competencies and certificates.

• Email: [email protected]
• LinkedIn: linkedin.com/in/muratko357

Tools: Google Cloud, Google DataFlow, Google BigQuery, Tableau

This project, built as the final project for the Google Business Intelligence Professional Certificate course, demonstrates my skills in Business Intelligence (BI), data pipelines, and dashboard creation. Key Achievements:

• Developed a comprehensive BI project plan.
• Constructed a data pipeline using Google DataFlow for efficient data movement from raw sources to BigQuery.
• Created an interactive dashboard in Tableau to visualize and analyze Minnesota interstate traffic volume data.
• Analyzed the impact of weather conditions, holidays, and time of day on traffic volume.
• Identified optimal periods for construction and repair activities based on traffic patterns. View Dashboard

Tools: Python, pandas, plotly, dash

I developed an interactive, web-based dashboard application that visualizes the performance of US domestic airlines in real time.

Tools: Python, numpy, pandas, matplotlib, seaborn, scipy, sklearn, time

I built a machine-learning classification model to predict whether it will rain tomorrow using Australian weather data. I evaluated various models, including Logistic Regression, Decision Tree, Random Forest, and Support Vector Machine, to determine the best fit based on accuracy and computation time.

Tools: Python, numpy, pandas, matplotlib, seaborn, sklearn

I performed an exploratory data analysis on LendingClub loan data using data visualization techniques. Then, I applied Random Forest and Decision Tree models to predict loan repayment outcomes, considering variables such as loan purpose, interest rate, monthly installments, borrower income, debt-to-income ratio, FICO score, and credit line age.

Tools: Python, pandas, matplotlib, seaborn, sklearn, tensorflow

Using the UCI Bank Authentication Data Set, I employed a Deep Neural Network Classifier to predict the authenticity of bank notes. The dataset includes features such as the variance, skewness, kurtosis, and entropy of Wavelet Transformed images.

Tools: Python, numpy, pandas, matplotlib, seaborn

I analyzed Uber pickup data from April 2014 in New York using data visualization and crosstabulation techniques. The analysis provides insights for business and drivers based on the geographic location and timing of the calls.

Tools: Tableau

I created various dashboards to answer business questions related to sales, profits, and shipment statuses of orders, applying design principles of data visualization.

Tools: ArcGIS

I analyzed the 2012 electoral data for California, which includes geographic information and vote counts for GMOs in food. I created a map displaying the normalized distribution of ‘yes’ votes by county. The PDF format of the map’s layout can be seen ( here ) and the map package is shared on my ArcGIS account here .

Tools: Python, pandas, matplotlib, seaborn, folium

I performed an exploratory data analysis on San Francisco’s 2016 crime dataset using visualization tools, crosstabulation, and crime mapping to display crime rates across city districts.

Tools: Python, pandas, BeautifulSoup, nltk, re, threading, time

For my Data Science & Machine Learning course, I created an automatic web-scraping and text summarization tool using Natural Language Processing (NLP). This tool collects and processes official COVID-19 reports and media summaries to help the public easily follow official advice and news.

Tools: Python, numpy, pandas, os, sys, scipy, imageio, matplotlib, tersorflow, pprint

I implemented the Neural Style Transfer (NST) algorithm to generate an artistic image of the Louvre museum in Paris in the style of a Claude Monet painting. The algorithm uses a pre-trained 19-layer VGG network model.

Tools: Python, numpy, argparse, os, matplotlib, scipy, PIL, tensorflow, keras, yolo utilities provided by deeplearning.ai

I applied the You Only Look Once (YOLO) model for car detection using a pre-trained dataset. YOLO is known for its high accuracy and real-time processing capabilities.

Tools: Python, numpy, pandas, keras, tensorflow, cv2, os, utilities provided by deeplearning.ai

I implemented the triplet loss function using a pretrained model to map face images into 128-dimensional encodings for face verification and recognition tasks. Face Verification is used for identity verification in applications like smartphone security systems, while Face Recognition identifies individuals by searching databases.

Areas of expertise

• Research methods
• Data analytics
• Crime analysis
• Developing policies for safety and crime prevention

Areas of experience

• Machine Learning
• Deep Learning
• GIS mapping

SQL, Python, R, Pandas, Numpy, SciPy, Matplotlib, Seaborn, Plotly, Scikit_learn, Statsmodels, Excel, Power BI, Tableau, IBM Watson Studio, R-Studio, IBM Cognos, ArcGIS, MS Suit, Google Suit, Jupyter Notebook, HTML & CSS, and Stata

Certified Courses

Google Business Intelligence Professional Certificate

Authorized by Google Issued by Coursera, 14 June 2024

In this intensive three-course program, I gained the skills necessary for entry-level Business Intelligence roles. While I already possessed most of these skills, I enrolled in the program to earn the certificate and gain deeper insights into BI industry applications. Throughout the course, I worked with tools such as Google Cloud, Google DataFlow, Google BigQuery, SQL, and Tableau.

IBM Data Analyst Professional Certificate

Authorized by IBM Issued by Coursera, 30 October 2021

This IBM Professional Certificate was earned after successfully completing 9 courses on various topics in Data Analytics. The courses included hands-on work with various data sources, project scenarios, and data analysis tools, including Excel, SQL, Relational Databases, Python, Jupyter Notebooks, and Cognos Analytics. I gained practical experience with data manipulation, data analysis, and data visualization. I demonstrated proficiency in applying different analytical techniques by analyzing real-world datasets, creating visualizations & interactive dashboards, and presenting reports to share findings of data analysis. This certificate equips me with skills for an entry-level role in data analytics.

Deep Learning Specialization

Authorized by DeepLearning.AI Issued by Coursera, 12 March 2020

This certificate was earned after successfully completing 5 courses. The courses covered neural network architectures, such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and strategies to improve them, such as Dropout, BatchNorm, and Xavier/He initialization. The courses also included their theoretical concepts, industry applications using Python and TensorFlow in real-world cases such as speech recognition, music synthesis, chatbots, machine translation, and natural language processing.

Data Science & Machine Learning

Issued by DeeploAI, 15 July 2020

This 10-month course, including a capstone project, covered Python for Data Science, Databases and SQL, Linear Algebra, Statistics, GIT, data pre-processing, Regression, Classification, Machine Learning Models, TensorFlow, and Keras, and more.

Other courses:

Data Analysis with R Programming

Authorized by Global Director of Google Career Certicates Issued by Coursera, 10 July 2022

Fundamentals of GIS

Authorized by University of California, Davis Issued by Coursera, 22 March 2021

Essential Design Principles for Tableau

Authorized by University of California, Davis Issued by Coursera, 22 January 2021

Excel Skills for Business: Essentials

Authorized by Macquarie University Issued by Coursera, 17 February 2020

Fitting Statistical Models to Data with Python

Authorized by University of Michigan Issued by Coursera, 7 February 2020

Using Databases with Python

Authorized by University of Michigan Issued by Coursera, 30 October 2019

SQL for Data Science

Authorized by University of California, Davis Issued by Coursera, 28 October 2019

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