Associate Data Scientist in Python
Certification from Data Camp for Course Track completion
Associate Data Scientist in Python
This Associate Data Scientist in Python certification validates practical skills in data wrangling, statistics, and machine learning with Python—demonstrating you can analyze real-world data and build end‑to‑end predictive solutions.
From Python basics to advanced machine learning, this certification track took me through every core step of becoming a data scientist. I learned to wrangle data with pandas, explore it with visualizations, and clean messy real‑world datasets. Then I dove into statistics, hypothesis testing, and experimental design to make evidence‑based decisions. Finally, I built and evaluated predictive models—from regression with statsmodels to tree‑based ensembles with scikit‑learn—gaining the confidence to tackle real business problems end to end.
List of all courses completed
- Introduction to Python
- Intermediate Python
- Data Manipulation with pandas
- Joining Data with pandas
- Introduction to Statistics in Python
- Introduction to Data Visualization with Matplotlib
- Introduction to Data Visualization with Seaborn
- Introduction to Functions in Python
- Python Toolbox
- Exploratory Data Analysis in Python
- Working with Categorical Data in Python
- Data Communication Concepts
- Introduction to Importing Data in Python
- Cleaning Data in Python
- Working with Dates and Times in Python
- Writing Functions in Python
- Introduction to Regression with statsmodels in Python
- Sampling in Python
- Hypothesis Testing in Python
- Experimental Design in Python
- Supervised Learning with scikit-learn
- Unsupervised Learning in Python
- Machine Learning with Tree-Based Models in Python
Project and assessments completed
- Investigating Netflix Movies (project)
- Exploring NYC Public School Test Result Scores (project)
- Visualizing the History of Nobel Prize Winners (project)
- Analyzing Crime in Los Angeles (project)
- Customer Analytics: Preparing Data for Modeling (project)
- Exploring Airbnb Market Trends (project)
- Modeling Car Insurance Claim Outcomes (project)
- Hypothesis Testing with Men’s and Women’s Soccer Matches (project)
- Predictive Modeling for Agriculture (project)
- Clustering Antarctic Penguin Species (project)
- Predicting Movie Rental Durations (project)
- Data Manipulation with Python (Signal assessment)
- Importing & Cleaning Data with Python (Signal assessment)
- Python Programming (Signal assessment)
What can I do with this?
With the Associate Data Scientist in Python track, I’ve developed the skills to tackle end-to-end analytical problems. I can import raw data from multiple sources, clean and transform it with pandas, and uncover clear, data-driven insights using exploratory data analysis, statistics, and compelling visualizations. On top of that, I can build and evaluate predictive models—including regression, classification, clustering, and tree-based ensembles—to solve realistic problems such as forecasting demand, measuring risk, or predicting customer behavior.
Through the projects in this track, I’ve experienced the full data science workflow in practice. I’ve worked with messy real-world datasets, from crime reports and NYC school performance to Airbnb listings, agricultural data, and movie rentals. For each scenario, I framed the problem, prepared and engineered features (including categorical variables and time-based data), explored patterns through visualization, trained and tuned models, and interpreted the results to make actionable recommendations. This hands-on practice has given me a repeatable, structured approach to solving data problems from start to finish.
My next steps are to deepen and specialize this foundation. I plan to build additional portfolio projects using public datasets that align with my interests, such as finance, healthcare, or marketing, to demonstrate how I apply these techniques in different domains. I also aim to strengthen adjacent skills like SQL, Git, and cloud platforms, and gradually move into more advanced tracks and certifications. Together, these steps will help me grow from an associate-level data scientist into someone who can design, ship, and maintain production-grade data solutions.
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My Story
From Curiosity to Craft: My Journey in Technology and Analytics
My name is Nuwan Hettiarachchi, and my journey has been guided by curiosity, service, and a strong belief in using technology to create meaningful impact.
I began my professional path working closely with data, systems, and people. Early on, I realized that I enjoyed solving practical problems—especially those where analytical thinking and real-world needs intersect. This led me into data analytics, automation, and software development, where I’ve spent years building tools that improve accuracy, efficiency, and decision-making.
A defining part of my journey has been 10 years of volunteer teaching at a charitable organization. Teaching reinforced my belief that knowledge is most powerful when shared. It strengthened my communication skills, patience, and ability to break down complex ideas—skills that continue to shape how I design systems and collaborate with teams today.
Professionally, I’ve worked across data analysis, reporting, and application development. One notable experience was developing a Human Resources appraisal system over two years using Visual Basic and SQL Server, where I translated business rules into reliable, user-friendly software. Projects like this deepened my appreciation for clean data, thoughtful design, and systems that support people—not just processes.
Over time, my work expanded into Python, SQL databases, analytics, and automation, with a growing focus on data integrity and insight-driven solutions. I enjoy building tools that reduce manual effort, surface meaningful patterns, and enable better decisions.
Outside of work, I value balance and mindfulness. I enjoy hiking, traveling, kayaking, and spending time in nature—activities that keep me grounded and curious.
Today, I’m focused on contributing within data science and analytics–driven environments, continuing to learn, mentor, and build solutions that are practical, ethical, and impactful.
Software Engineer & Data Science| SQL, Analytics, and AI Solutions
Nuwan Hettiarachchi
I bring strong experience in data analytics and data engineering, with a focus on SQL-driven data preparation, data quality, and scalable processing pipelines. My background includes working with large, complex datasets, supporting business intelligence, and applying data governance principles such as profiling, lineage, and documentation. I am known for collaborating effectively across teams to design clear, reliable data solutions that support informed decision-making.
Phone
(604) 256-2432
Surrey BC, Canada