Certificates
Machine Learning, Stanford University, CA (See course syllabus)
Machine Learning Foundations: A Case Study Approach, Washington State University, WA (See course syllabus)
Python for Data Science and Machine Learning
Managing Big Data With MySQL, Duke University, NC
Data Visualization and Communication with Tableau, Duke University, NC (See course syllabus)
" DataFrames with pandas
Introduction to Databases, Stanford University, CA (See course syllabus)
Introduction to Python for Data Science, Microsoft, WA (See course syllabus)
Lean Concepts and Applications, Northeastern University, MA (See course syllabus)
WEEK-1: How Data Analysts ask the right questions to ensure project success
WEEK-2: Data Visualization with Tableau
WEEK-3: Dynamic Data Manipulation and Presentation in Tableau
WEEK 4: Your Communication Toolbox: Visualizations, Logic, and Stories
WEEK 5: Final Project
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WEEK-1: Introduction, Linear Regression with One Variable, Linear Algebra Review
WEEK-2: Linear Regression with Multiple Variables, Octave/Matlab Tutorial
WEEK-3: Logistic Regression, Regularization
WEEK 4: Neural Networks: Representation
WEEK 5: Neural Networks: Learning
WEEK 6: Advice for Applying Machine Learning, Machine Learning System Design
WEEK 7: Support Vector Machines
WEEK 8: Unsupervised Learning, Dimensionality Reduction / Principal Component Analysis
WEEK 9: Anomaly Detection, Recommender Systems
WEEK 10: Large Scale Machine Learning
WEEK 11: Application Example: Photo OCR
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WEEK 1: Introduction
WEEK 2: Regression: Predicting House Prices
WEEK 3: Classification: Analyzing Sentiment
WEEK 4: Clustering and Similarity: Retrieving Documents
WEEK 5: Recommending Products
WEEK 6: Deep Learning: Searching for Images
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Section 1: Python Basics
Section 2: Python Lists
Section 3: Functions and Packages
Section 4: Numpy
Section 5: Matplotlib
Section 6: Control flow and Pandas
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Week-1: Introduction, Relational Databases, XML Data
Week-2: JSON Data , Relational Algebra
Week-3: SQL
Week-4: Relational Design Theory
Week-5: Querying XML
Week-6: Unified Modeling Language, Indexes, Transactions, Constraints and Triggers
Week-7: Constraints and Triggers
Week-8: Views, Authorization
Week-9: Recursion, On-Line Analytical Processing
Week-10: NoSQL Systems
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