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Applied Data Science with Python Specialization

A thorough and practice-oriented specialization that empowers you with essential data science tools and real-world applications using Python.

access

Lifetime

level

Beginner

certificate

Certificate of completion

language

English

What will you learn in Applied Data Science with Python Specialization Course

  • Use Python and libraries like Pandas, Matplotlib, Scikit-learn, NLTK, and NetworkX for advanced data analysis.

  • Perform inferential statistical analysis and evaluate sampling accuracy.

  • Create effective data visualizations and interpret multivariate patterns.

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  • Build predictive models using supervised and unsupervised machine learning.

  • Transform text data and analyze social networks using real-world datasets.

Program Overview

Module 1: Introduction to Data Science in Python

⏳ 4 weeks
Topics: Python essentials (lambdas, CSV handling), Pandas for data manipulation and cleaning, basic statistics and t-tests.
Hands-on: Explore DataFrame operations like groupby, merging, and pivot tables using real datasets.

Module 2: Applied Plotting, Charting & Data Representation in Python

⏳ 4 weeks
Topics: Design principles of good visualizations, chart selection, Matplotlib functions for varied use cases.
Hands-on: Create visualizations using Matplotlib that communicate data insights cleanly.

Module 3: Applied Machine Learning in Python

⏳ 4 weeks
Topics: Difference between ML and statistics, clustering, predictive model building, feature engineering.
Hands-on: Train models like decision trees and clustering algorithms, evaluate and compare performance.

Module 4: Applied Text Mining in Python

⏳ 4 weeks
Topics: Text parsing, NLP fundamentals, topic modeling, usage of NLTK for text processing.
Hands-on: Write code to clean text, classify documents, and extract topic insights from collections.

Module 5: Applied Social Network Analysis in Python

⏳ 4 weeks
Topics: Network representation using NetworkX, node centrality, connectivity measures, network dynamics.
Hands-on: Analyze network graphs, compute centrality metrics, and model network evolution.

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Job Outlook

  • Widely applicable across roles like data scientist, analyst, ML engineer, or research data specialist.

  • Python proficiency and domain experience are essential for data-driven roles across industries.

  • Salaries range from ₹8–20 LPA (India) and $80–$150K (US), depending on experience and specialization.

  • Builds a portfolio-ready foundation for freelance and remote analytics work.

9.7Expert Score
Highly Recommendedx
A comprehensive, skill-based specialization that balances depth and practical application. Ideal for learners with Python basics looking to level up in real-world data tasks.
Value
9.5
Price
9.3
Skills
9.8
Information
9.7
PROS
  • Hands-on, project-aligned modules across key data science domains.
  • Strong emphasis on applied methods over pure theory.
  • Taught by respected University of Michigan faculty.
CONS
  • Not for absolute beginners—prior Python knowledge is expected.
  • Some modules (like text mining or network analysis) may feel surface-level.

Specification: Applied Data Science with Python Specialization

access

Lifetime

level

Beginner

certificate

Certificate of completion

language

English

Applied Data Science with Python Specialization
Applied Data Science with Python Specialization
Course | Career Focused Learning Platform
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