Shagofta Shabashkhan

Highly motivated graduate student pursuing a Master's in Data Science, equipped with a strong foundation in Python Programming, statistical analysis, machine learning, and data manipulation. Eager to apply acquired skills and knowledge to contribute effectively to data-driven projects. Proactive learner staying up-to-date with industry trends and emerging technologies. Detail-oriented with an analytical mindset, capable of effectively communicating insights. Seeking a Junior Data Scientist role to apply theoretical knowledge and practical expertise, making valuable contributions to data-driven initiatives while further honing skills in a professional setting.

• Deep Learning Specialization from Deeplearning.AI Acquired in-depth knowledge and practical skills in deep learning algorithms, neural networks, and their applications in areas such as computer vision and natural language processing
• Machine Learning from Stanford University: Completed an intensive program that covered essential concepts and techniques in machine learning, including regression, classification, clustering, and model evaluation
• Python Programming Language from Pierian Data: Gained proficiency in Python, a versatile programming language widely used in data analysis, machine learning, and automation tasks, enabling efficient data manipulation and model development
• Machine Learning Business Professional from Google Cloud: Acquired a comprehensive understanding of machine learning concepts, frameworks, and best practices within the context of business applications

• 5-time General Champion in Sports
• Captain and team leader, inspiring victories
• State-level Basketball Award recipient
• Miss Dharwad Fashion Show Winner
• Student Academic Representative

Watching Documentaries

Dance

Singing

Basketball

Drawing

1)  Analysis of Carbon-Dioxide Emission 

• Conducted in-depth analysis of carbon dioxide emission data using R programming
• Utilized faceting to analyze emission patterns by geographic regions, industries, and time periods
• Employed radar charts to assess the impact of variables on carbon dioxide emissions, enabling effective decision-making
• Utilized donut charts to visualize the distribution of emission sources across sectors or activities

2)  Analysis of the Effects of Depression 

• Conducted comprehensive analysis of the effects of depression on physical and psychological factors
• Utilized IBM SPSS for statistical analysis, including regression, correlation, and t-tests
• Identified significant associations between depression and menopause, loneliness, gender, blood pressure, and smoking
• Provided valuable insights and recommendations to understand the impact of depression on well-being

3)  Analysis of Social Deprivation Indices over Five Years 

• Analyzed changes in social deprivation indices over a five-year period using the IMD dataset
• Utilized statistical techniques, including descriptive statistics, inferential statistics, and time series analysis
• Investigated trends and patterns in social deprivation across different regions
• Produced clear visualizations and reports to effectively communicate findings

4) Titanic Dataset

• Analyzed the Titanic dataset using Knime Analytics, exploring demographics and survival rates
• Employed statistical modelling techniques to uncover patterns and relationships within the dataset
• Developed accurate predictive models using decision trees in Knime
• Effectively communicated insights through impactful data visualizations

5)  Edge Detection with Motion Detection using Computer Vision 

• Developed a computer vision project for accurate edge detection and moving object segmentation using OpenCV, Laplacian Filter, and Optical Flow algorithm
• Implemented advanced edge detection techniques, enhancing the visual clarity of detected edges
• Integrated Optical Flow algorithm for motion detection and segmentation of moving objects in video sequences

6) Real-time Video Recorder using OpenCV 

• Developed a real-time video recorder application using OpenCV to capture and store video
• Implemented user-friendly functionality for starting and stopping video recording with ease

7)  Hostel Management System  

• Developed a comprehensive Hostel Management System to maintain records of hostel students, including attendance, fees, and room allocation
• Designed an intuitive user interface using CSS, HTML, and JavaScript to ensure a seamless user experience
• Implemented a MySQL database to store and retrieve student information, attendance records, fee details, and room allocation data

Internet: Boon or Bane  

• Explored the advantages of the internet, including easy access to information, communication opportunities, and convenience in daily life
• Examined the disadvantages of the internet, such as cybercrime, online privacy concerns, and the potential for addiction or information overload

Data Ethics: Data Biasing  

• Highlighted the importance of addressing data biasing in research, emphasizing fairness and decision-making
• Presented historical examples showcasing the consequences of data biasing, emphasizing the need for ethical data practices

Types of Sampling  

• Explored cluster sampling, simple random sampling, and convenience sampling as different techniques in data collection
• Discussed the importance of representative results through cluster sampling and the reliability of unbiased data using simple random sampling, while acknowledging the limitations and potential biases of convenience sampling