Designed for aspiring data scientists, engineers, and researchers, this hands-on program guides you through the entire data science process—from acquiring and transforming real-world data to building, validating, and deploying machine learning models. Through engaging, example-driven lessons and practical exercises using Python and its robust ecosystem of libraries, you'll gain the essential skills to analyze complex datasets, extract actionable insights, and create impactful data-driven applications—no advanced math or statistics background required.
Data Science Fundamentals, Part 1 Specialization
Data Science Fundamentals, Part 1 Specialization
Basic Concepts, Data Wrangling, Databases--Python. Gain hands-on experience in real-world data acquisition, parsing, and ML applications.
Instructor: Pearson
Included with 
Get in-depth knowledge of a subject
Beginner level
Recommended experience
1 month at 5 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
Beginner level
Recommended experience
1 month at 5 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Acquire, clean, and structure real-world data from diverse sources using Python, APIs, and relational databases.
Analyze, visualize, and model data using industry-standard libraries such as Pandas, NumPy, SciPy, Statsmodels, and Scikit-learn.
Build, validate, and deploy machine learning models, applying best practices in data science to solve practical, real-world problems.
Overview
Skills you'll gain
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
Recently updated!
August 2025
7 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from Pearson
Specialization - 3 course series
What you'll learn
Develop a strong foundation in data science concepts, theory, and the practical application of Python’s data ecosystem.
Acquire, manipulate, and analyze real-world datasets using industry-standard tools and libraries.
Build and evaluate machine learning models, including recommendation engines, with hands-on projects.
Master the end-to-end data science process, from data acquisition to visualization and effective communication of results.
Skills you'll gain
Data Science, Data Manipulation, Python Programming, NumPy, Data Analysis, Scikit Learn (Machine Learning Library), Machine Learning, Machine Learning Algorithms, Programming Principles, Exploratory Data Analysis, Applied Machine Learning, Computational Thinking, and Pandas (Python Package)
What you'll learn
Master the ETL (Extract, Transform, Load) process for seamless data acquisition and integration.
Acquire practical skills in sourcing data from APIs, web scraping, and managing data lineage.
Parse and transform diverse data formats (XML, JSON) for structured analysis.
Build and apply data models using object-oriented programming to streamline data workflows.
Skills you'll gain
Data Pipelines, Data Transformation, Extensible Markup Language (XML), Extract, Transform, Load, Data Modeling, Data Integration, Application Programming Interface (API), JSON, Web Scraping, Relational Databases, and Object Oriented Programming (OOP)
What you'll learn
Master the fundamentals of relational databases and persistent data storage.
Build and optimize ETL pipelines using Python and object-relational mappers.
Apply data validation techniques to ensure data quality and integrity.
Utilize Pandas for effective data exploration, transformation, and statistical analysis.
Skills you'll gain
Extract, Transform, Load, Data Validation, Data Transformation, Relational Databases, Descriptive Statistics, Object-Relational Mapping, Pandas (Python Package), Data Storage Technologies, Data Manipulation, Databases, SQL, Data Cleansing, Exploratory Data Analysis, Data Processing, Data Integrity, Data Analysis, Database Management, Data Pipelines, and Data Quality
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
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Frequently asked questions
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
More questions
Financial aid available,