Mehedi Hasan Data Analysist, Researcher, PhD Student,
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Hi, I’m a graduate student and data science enthusiast with expertise in data analysis, Python programming (Pandas, NumPy, Scikit-learn, TensorFlow), and advanced analytical techniques such as machine learning, time series forecasting, NLP, and survival analysis. My experience includes roles as a Research Assistant, where I authored peer-reviewed papers and built predictive models, and a Data Analyst Intern, where I automated sentiment analysis and improved operational efficiency by 15% through data-driven insights. Proficient in tools like SQL, Tableau, and Git, I hold certifications in IBM Data Science and Deep Learning, and I’ve executed projects ranging from customer segmentation using K-means clustering to developing COVID-19 trend predictors with ARIMA models. With an M.Sc. in Data Science and a thesis focused on Bayesian inference applications, I specialize in transforming raw data into actionable narratives through rigorous analysis, academic writing, and dynamic visualization. Let’s collaborate to turn complex challenges into impactful solutions!

Subjects

Thesis Writing Bachelors/Undergraduate-Doctorate/PhD
Data analysis and visualization Bachelors/Undergraduate-Doctorate/PhD
Data Analysis in R/Python Expert
Sample size estimation Bachelors/Undergraduate-Doctorate/PhD
Thesis and Dissertation

Experience

research analysis (Mar, 2022–Present) at Begum Rokeya University, Rangpur

Data Analysis
Thesis Writing
Projects Managements
Mentoring
Python Class

Education

Bachelor of science (Jan, 2019–now) from Begum Rokeya University, Rangpur
Bachelor of science (Jan, 2019–now) from Changsha University of Science and Technology
Higher Secondary (Jan, 2016–Dec, 2018) from Rangpur govt. city college
Secondary (Jan, 2014–Dec, 2016) from Chandpara B.L high school

Fee details

৳1,000–3,600/hour (US$8.15–29.33/hour)

Charge can vary content, time and place. Don't worry contact with me. I consider your payment.

Courses offered

Environmental Data Analysis using Python Steps by Steps
- US$30
- Duration: 10 Hours
- Delivery mode: Flexible as per the student
- Group size: Individual
- Instruction language: English, Bengali
- Certificate provided: Yes
Master Python to tackle environmental challenges! This step-by-step course teaches you to analyze air quality, biodiversity, and climate data using Pandas, GeoPandas, and ML tools. Transform raw datasets into actionable insights—no prior coding expertise required!

1. Python Basics for Environmental Science
- Setting up Python & Jupyter Notebooks
- Essential libraries: Pandas, NumPy, Matplotlib, Seaborn
- Importing/exporting environmental data (CSV, NetCDF, GIS formats)

2. Data Cleaning & Preprocessing
- Handling missing sensor data, outliers, and time-series gaps
- Merging datasets (e.g., satellite data + ground measurements)
- Geospatial data wrangling with GeoPandas

3. Exploratory Environmental Analysis
- Visualizing pollution trends, deforestation maps, and species distributions
- Statistical summaries for ecological datasets
- Correlation analysis (e.g., CO2 vs. temperature trends)

4. Advanced Spatial Analysis
- Mapping climate change hotspots with Folium/Plotly
- Zonal statistics for protected areas or urban zones
- Time-lapse animations of environmental changes

5. Machine Learning for Sustainability
- Predicting air quality using regression models
- Classifying land cover from satellite imagery (Scikit-learn)
- Clustering regions by pollution vulnerability (K-means)

6. Climate & Biodiversity Modeling
- ARIMA/Prophet for forecasting temperature/precipitation
- Species distribution modeling (SDMs) with ML
- Ocean acidification trend analysis

7. Reproducible Research & Reporting
- Automate workflows with Python scripts
- Create interactive dashboards (Panel/Streamlit)
- Export publication-ready graphs and maps

8. Capstone Projects
- Build a wildfire risk prediction model
- Analyze global GHG emissions by sector
- Track coral reef health using open-source biodiversity data
How to Write an Academic Thesis for Bachelor’s and Master’s: From Proposal to Defense
- US$40
- Duration: 2 Weeks
- Delivery mode: Flexible as per the student
- Group size: Individual
- Instruction language: English, Bengali
- Certificate provided: Yes
Struggling to structure your thesis or meet academic standards? This step-by-step course demystifies the entire thesis-writing process, from choosing a research topic to defending your work. Learn to craft a compelling proposal, organize arguments, and avoid common pitfalls—perfect for undergraduates and graduate students aiming for clarity, rigor, and impact.

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Course Content
1. Understanding Thesis Requirements
- Differences between Bachelor’s vs. Master’s theses
- Aligning with university guidelines and rubrics
- Setting realistic timelines and milestones

2. Topic Selection & Research Design
- Brainstorming impactful, feasible research questions
- Conducting a preliminary literature review
- Building a theoretical framework

3. Writing a Winning Proposal
- Structuring objectives, hypotheses, and methodology
- Justifying significance and innovation
- Pitching to advisors/committees

4. Research Methodology Mastery
- Quantitative vs. qualitative approaches
- Data collection tools (surveys, experiments, interviews)
- Ethical considerations and permissions

5. Literature Review Deep Dive
- Synthesizing sources thematically/chronologically
- Identifying gaps and building your contribution
- Avoiding plagiarism with proper citation (APA/MLA/Chicago)

6. Writing & Structuring Your Thesis
- Crafting clear introductions, literature reviews, and conclusions
- Presenting results (tables, graphs, visualizations)
- Linking analysis to research questions

7. Advanced Data Analysis & Interpretation
- Using tools like SPSS, R, or Python for analysis
- Drawing meaningful conclusions from findings
- Addressing limitations and future research

8. Editing, Formatting, and Proofreading
- Academic writing style: clarity, conciseness, formality
- Formatting tips (headings, fonts, references)
- Tools: Grammarly, LaTeX, Zotero/Mendeley

9. Preparing for the Defense
- Creating a persuasive presentation (PowerPoint/Canva)
- Anticipating committee questions
- Handling feedback and revisions

10. Avoiding Common Pitfalls
- Managing writer’s block and stress
- Overcoming data collection challenges
- Revising drafts efficiently

Bonus Resources:
- Thesis templates (Word/LaTeX)
- Checklist for each chapter
- Sample successful proposals and defense slides
- Time management worksheets