GitHub - maicat11/Computing-for-Data-Analysis: This course is a hands-on introduction to programming techniques relevant to data analysis and machine learning. Most of the programming exercises will be based on Python and SQL.

CSE 6040x: Intro to Computing for Data Analysis

Instructor: Professor Richard (Rich) Vuduc Co-creators: Vaishnavi Eleti and Rachel Wiseley

Course description.

This course is your hands-on introduction to programming techniques relevant to data analysis and machine learning. Most of the programming exercises will be based on Python and SQL.

What will you learn?

You will build, "from scratch," the basic components of a data analysis pipeline: collection, preprocessing, storage, analysis, and visualization. You will see many examples of high-level data analysis questions, concepts and techniques for formalizing those questions into mathematical or computational tasks, and methods for translating those tasks into code. Beyond programming languages and best practices, you’ll learn elementary data processing algorithms, notions of program correctness and efficiency, and numerical methods for linear algebra and mathematical optimization.

Philosophy and approach.

The basic philosophy of this course is that you'll learn the material best by a combination of reading, thinking, and most importantly, actively doing. Therefore, you should make an effort to complete all assignments, including any "optional" parts.

Name		Name	Last commit message	Last commit date
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.DS_Store		.DS_Store
NYC-311-2M.db		NYC-311-2M.db
Notebook0-basics.ipynb		Notebook0-basics.ipynb
Notebook10_NumpyMatrix_part2.ipynb		Notebook10_NumpyMatrix_part2.ipynb
Notebook10_NumpyMatrix_part3.ipynb		Notebook10_NumpyMatrix_part3.ipynb
Notebook10_NumpyScipy_part1.ipynb		Notebook10_NumpyScipy_part1.ipynb
Notebook11_MarkovChainAnalysis.ipynb		Notebook11_MarkovChainAnalysis.ipynb
Notebook11_MarkovChainAnalysis_Ranking.ipynb		Notebook11_MarkovChainAnalysis_Ranking.ipynb
Notebook12_Algoriths_LinearLeastSq_part3.ipynb		Notebook12_Algoriths_LinearLeastSq_part3.ipynb
Notebook12_Cost_part3.ipynb		Notebook12_Cost_part3.ipynb
Notebook12_Gradients_part2.ipynb		Notebook12_Gradients_part2.ipynb
Notebook12_LinReg_ModelFitting_part1.ipynb		Notebook12_LinReg_ModelFitting_part1.ipynb
Notebook12_LinerRegNotes.ipynb		Notebook12_LinerRegNotes.ipynb
Notebook12_PerturbationTheory.ipynb		Notebook12_PerturbationTheory.ipynb
Notebook12_ThetaLMS.ipynb		Notebook12_ThetaLMS.ipynb
Notebook13_LogisticRegression.ipynb		Notebook13_LogisticRegression.ipynb
Notebook13_NumpyMatrixManipulation.ipynb		Notebook13_NumpyMatrixManipulation.ipynb
Notebook14_KMeans_Clustering.ipynb		Notebook14_KMeans_Clustering.ipynb
Notebook15_Compression_via_PCA&SVD.ipynb		Notebook15_Compression_via_PCA&SVD.ipynb
Notebook15_SVDimage_compression.ipynb		Notebook15_SVDimage_compression.ipynb
Notebook16_EiganFaces.ipynb		Notebook16_EiganFaces.ipynb
Notebook1_part1-collections.ipynb		Notebook1_part1-collections.ipynb
Notebook1_part2-more_exercises.ipynb		Notebook1_part2-more_exercises.ipynb
Notebook4_part1_floating_points.ipynb		Notebook4_part1_floating_points.ipynb
Notebook4_part2_floatingPoints.ipynb		Notebook4_part2_floatingPoints.ipynb
Notebook5_part1_RegEx.ipynb		Notebook5_part1_RegEx.ipynb
Notebook5_part2_RegExYelp.ipynb		Notebook5_part2_RegExYelp.ipynb
Notebook5_part3_RegEx_hard.ipynb		Notebook5_part3_RegEx_hard.ipynb
Notebook6_part1_web_mining.ipynb		Notebook6_part1_web_mining.ipynb
Notebook6_part2_BeautifulSoup.ipynb		Notebook6_part2_BeautifulSoup.ipynb
Notebook6_part3_webMiningAPIs.ipynb		Notebook6_part3_webMiningAPIs.ipynb
Notebook7_Pandas_TidyData.ipynb		Notebook7_Pandas_TidyData.ipynb
Notebook8_bokeh_seaborn.ipynb		Notebook8_bokeh_seaborn.ipynb
Notebook9_SQL_Part2.ipynb		Notebook9_SQL_Part2.ipynb
Notebook9_SQL_relational_DBs.ipynb		Notebook9_SQL_relational_DBs.ipynb
README.md		README.md
Supplemental_notebook.ipynb		Supplemental_notebook.ipynb
part1.ipynb		part1.ipynb

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CSE 6040x: Intro to Computing for Data Analysis

Course description.

What will you learn?

Philosophy and approach.

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