Data & AI · 42Beginner

Data Miner

Analysts who extract patterns from large volumes of text and data.

Python, text and pattern mining, clustering, anomaly detection and applied data science.

410hours of coursework

41weeks at 10 h

4steps

19courses

3universities

Target skills

Data VisualizationModel EvaluationData CleansingData PresentationPython ProgrammingData AnalysisText MiningNatural Language ProcessingData MiningPlot (Graphics)Supervised LearningData Preprocessing

Skill labels as listed on Coursera.

Target jobs

Data miner
Text and data analyst
Data scientist

Progression

Specialization · 5 courses

Python for Everybody Specialization

79 h

University of MichiganBeginnerPython, SQL, SQLite

Stated prerequisites: No prerequisites; designed as an on-ramp to programming

Show the 5 courses

Course	Level	Length	Rating (reviews)
Programming for Everybody (Getting Started with Python)	Beginner	17 h	4.8 (233,775)
Python Data Structures	Beginner	20 h	4.9 (97,365)
Using Python to Access Web Data	Beginner	19 h	4.8 (44,591)
Using Databases with Python	Beginner	14 h	4.8 (21,659)
Capstone: Retrieving, Processing, and Visualizing Data with Python	Beginner	9 h	4.7 (14,483)

Specialization · 6 courses

Data Mining

129 h

University of Illinois Urbana-ChampaignIntermediateTableau

Stated prerequisites: Comfort with programming; basic probability and statistics

Show the 6 courses

Course	Level	Length	Rating (reviews)
Data Visualization	—	16 h	4.5 (1,410)
Text Retrieval and Search Engines	—	31 h	4.5 (967)
Text Mining and Analytics	—	33 h	4.5 (741)
Pattern Discovery in Data Mining	—	17 h	4.3 (327)
Cluster Analysis in Data Mining	—	17 h	4.5 (411)
Data Mining Project	—	15 h	4.5 (51)

3
Specialization · 3 courses
Data Mining Foundations and Practice
65 h
University of Colorado BoulderIntermediatePython
Stated prerequisites: Some data experience, Python, data structures and algorithms, basic probability
Show the 3 courses
Course Level Length Rating (reviews)
Data Mining Pipeline Intermediate 22 h 3.9 (123)
Data Mining Methods Intermediate 24 h 4.3 (76)
Data Mining Project Intermediate 19 h 4.4 (33)

Course	Level	Length	Rating (reviews)
Data Mining Pipeline	Intermediate	22 h	3.9 (123)
Data Mining Methods	Intermediate	24 h	4.3 (76)
Data Mining Project	Intermediate	19 h	4.4 (33)

Specialization · 5 courses

Applied Data Science with Python

137 h

University of MichiganIntermediatePython, pandas, Matplotlib, scikit-learn, NLTK, NetworkX

Stated prerequisites: Basic Python or programming background

Show the 5 courses

Course	Level	Length	Rating (reviews)
Introduction to Data Science in Python	Intermediate	30 h	4.5 (27,302)
Applied Plotting, Charting & Data Representation in Python	Intermediate	24 h	4.5 (6,290)
Applied Machine Learning in Python	Intermediate	32 h	4.6 (8,814)
Applied Text Mining in Python	Intermediate	25 h	4.2 (3,827)
Applied Social Network Analysis in Python	Intermediate	26 h	4.6 (2,730)

With Coursera Plus

This path takes 410 hours, about 9 months at 10 hours a week. A Coursera Plus subscription gives access to most of its courses during that time.

Discover Coursera Plus

Projects to build

After step 2

Corpus topics

Extract the main topics of an article corpus with a topic model.

After step 3

Association rules

Find products often bought together in a public receipts dataset.

After step 3

Fraud detection

Spot abnormal transactions in an anonymised banking dataset.

Free textbooks

Python for EverybodyCharles R. SeveranceFree, CC BY 4.0

Python for Data Analysis, 3rd ed.Wes McKinneyOpen access online

An Introduction to Statistical Learning (Python)G. James, D. Witten, T. Hastie, R. Tibshirani, J. TaylorFree PDF