IBM Data Science Professional Certificate
Completed by ZAINAB KHALEEL IBRAHIM KARAM on February 8, 2026
Verified learner ·
Badge ID: qWxZcXsdRu-sWXF7HYbvJg
About this Badge
In this program, you’ll develop the skills, tools, and portfolio to have a competitive edge in the job market as an entry-level data scientist in as little as 4 months. No prior knowledge of computer science or programming languages is required. Data science involves gathering, cleaning, organizing, and analyzing data with the goal of extracting helpful insights and predicting expected outcomes. The demand for skilled data scientists growing and you will be ready.
Learning objectives
- Utilize Python and its libraries (NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn) to perform data manipulation, analysis, and visualization, and build predictive models.
- Develop and implement machine learning models using Python, including regression, classification, clustering, and dimensionality reduction techniques, and evaluate their performance through cross-validation and regularization.
- Apply SQL to manage and query databases, perform data wrangling, and integrate SQL with Python for data science tasks, including building complex queries and working with real-world datasets.
- Demonstrate proficiency in data science methodologies, including data collection, exploratory data analysis, model development, and reporting, through hands-on projects and capstone experiences.
Skills learned
- Interactive Data Visualization
- Applied Machine Learning
- Exploratory Data Analysis
- Computer Programming Tools
- Relational Databases
- Data Visualization Software
- Company, Product, and Service Knowledge
- Open Source Technology
- Geospatial Information and Technology
- Natural Language Processing
- Decision Tree Learning
- Box Plots
- Dimensionality Reduction
- Heat Maps
- Scatter Plots
- Query Languages
- Stored Procedure
- Responsible AI
- Peer Review
- Artificial Intelligence
- Digital Transformation
- Problem Solving
- Analytical Skills
- Interviewing Skills
- Restful API
- Transaction Processing
- User Feedback
- Predictive Modeling
- Version Control
- Professional Networking
- Web Scraping
- Software Development Methodologies
- R Programming
- Supervised Learning
- Data Synthesis
- Data Wrangling
- Programming Principles
- Python Programming
- Deep Learning
- Unsupervised Learning
- Generative AI
- Data Mining
- Data Presentation
- Statistical Modeling
- Big Data
- Data Structures
- Feature Engineering
- Regression Analysis
- Job Analysis
- Machine Learning
- Cloud Computing
- Dashboard
- Seaborn
- Data Collection
- Data Cleansing
- Data Literacy
- Data Manipulation
- Professional Development
- Histogram
- Jupyter
- Plotly
- Presentations
- GitHub
- JSON
- Matplotlib
- NumPy
- Data Processing
- Statistical Analysis
- Computer Programming
- Data Ethics
- Data Transformation
- Data Science
- Portfolio Management
- Writing
- Data Visualization
- Data Modeling
- Business Process
- Business Research
- Databases
- Recruitment
- SQL
- Automation
- Communication
- Business Analysis
- Data Analysis
- Skills section collapsed. Showing 6 of 85 skills.
Learning content completed
Some of the content and skills presented have been contributed by the content provider.