Applied Data Science Specialization

A full-stack beginner-friendly data science program teaching practical Python, ML, dashboards, NLP, and network analysis—all in one career-oriented specialization.

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access	Lifetime
level	Beginner
certificate	Certificate of completion
language	English

#Coursera

Description
Additional information

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).

9.7Expert Score

Highly Recommendedx

This IBM Specialization provides a well-rounded foundation—from Python coding to visualization, ML, NLP, and network analysis—bundled in hands-on labs and real-data projects. Ideal for constructing a professional data science skill set, though advanced learners may seek deeper specialization later.

Value

Price

9.2

Skills

9.4

Information

9.5

PROS

Hands-on labs on IBM Cloud and project-based learning.
Balanced skillset: Python, ML, visualization, NLP, and network analysis.
Capstone project demonstrates real industry-style competencies.

CONS

Some basic concepts may feel paced slowly if you already have Python or ML experience.
Limited focus on advanced topics like deep learning, big data tools, or model deployment pipelines.