What will you learn in Applied Data Science Specialization Course
Build foundational Python skills for data science (variables, control flow, Pandas, NumPy, web scraping).
Perform data wrangling and exploratory analysis, including handling missing data and feature engineering.
Create interactive visualizations and dashboards using Matplotlib, Seaborn, Plotly, and Dash.
Apply machine learning techniques: logistic regression, SVMs, decision trees, KNN, and model selection.
Program Overview
Course 1: Python for Data Science, AI & Development
⏳25 hours
- Python programming basics, REST APIs, web scraping, Jupyter notebook usage, Pandas & NumPy fundamentals.
Course 2: Python Project for Data Science
⏳8 hours
- Apply Python skills to real project scenarios, including data extraction and dashboard creation using Plotly and Pandas.
Course 3: Data Analysis with Python
⏳16 hours
- Clean, transform, and analyze datasets using Pandas and Scikit‑Learn; build regression models.
Course 4: Data Visualization with Python
⏳20 hours
- Build impactful visuals using Matplotlib, Seaborn, Folium, and interactive dashboards with Plotly Dash.
Course 5: Applied Data Science Capstone
- Real-world multi-model classification project (SVM, logistic regression, decision trees) to predict outcomes (e.g., SpaceX rocket reuse).
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Job Outlook
Ideal for early-career roles like Data Analyst, Junior Data Scientist, BI Analyst, or Python Developer for Data.
In-demand across sectors—healthcare, finance, retail, tech, government—for analytics, predictive modeling, reporting, and data storytelling.
Capstone experience demonstrates modeling and visualization competence—valuable for hiring assessments and portfolio work.
Certification recognized in partner programs like IBM’s Data Science Professional Certificate and counts toward ACE® credit (up to 12 college credits).
Specification: IBM Applied Data Science Specialization
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FAQs
- No advanced coding background is required.
- Basic Python familiarity is helpful but not mandatory.
- The course teaches Python fundamentals along the way.
- Hands-on labs reinforce coding through practice.
- Even complete beginners can progress with consistent effort.
- Yes, datasets are drawn from real domains like space tech, finance, and healthcare.
- Projects mimic practical data science challenges.
- Web scraping and APIs add real-world data experience.
- Capstone project uses genuine classification problems.
- Helps build a strong, portfolio-ready skill set.
- You’ll use IBM Cloud resources during labs.
- Work with Jupyter notebooks hosted online.
- No need for complex local setup.
- Skills are transferable to other cloud platforms.
- Experience mirrors modern industry workflows.
- Combines Python, visualization, and ML in one track.
- More hands-on than many theory-focused programs.
- Includes capstone for applied project experience.
- Recognized by IBM and ACE for credit transfer.
- Stronger industry tie-ins than generic bootcamps.
- Prepares you for Data Analyst and Junior Data Scientist positions.
- Supports career paths in BI analysis and Python development.
- Skills apply in healthcare, finance, retail, and government.
- Capstone project demonstrates real-world readiness.
- Certification adds credibility to job applications.
