What will you learn in Applied Data Science Specialization Course
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Build foundational Python skills for data science (variables, control flow, Pandas, NumPy, web scraping).
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Perform data wrangling and exploratory analysis, including handling missing data and feature engineering.
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Create interactive visualizations and dashboards using Matplotlib, Seaborn, Plotly, and Dash.
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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
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Ideal for early-career roles like Data Analyst, Junior Data Scientist, BI Analyst, or Python Developer for Data.
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In-demand across sectors—healthcare, finance, retail, tech, government—for analytics, predictive modeling, reporting, and data storytelling.
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Capstone experience demonstrates modeling and visualization competence—valuable for hiring assessments and portfolio work.
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Certification recognized in partner programs like IBM’s Data Science Professional Certificate and counts toward ACE® credit (up to 12 college credits).
Explore More Learning Paths
Enhance your applied data science skills with these hand-picked courses designed to help you leverage tools, methodologies, and foundational concepts to solve real-world data challenges.
Related Courses
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Tools for Data Science Course – Gain proficiency in Python, SQL, and other essential tools for data analysis and visualization.
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Data Science Methodology Course – Learn the structured approach to data science projects, from problem definition to solution implementation.
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Foundations of Data Science Course – Build strong foundational knowledge in statistics, data analysis, and core data science concepts.
Related Reading
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What Is Data Management? – Explore how proper data management supports effective analytics and applied data science projects.
