Stanford University
Machine Learning
Key Learnings: Machine Learning Basics, Supervised Learning, Unsupervised Learning, Regression, Back Propagation, KNN, Neural Networks, Recommender Systems, SVM.
Key Learnings: Machine Learning Basics, Supervised Learning, Unsupervised Learning, Regression, Back Propagation, KNN, Neural Networks, Recommender Systems, SVM.
Key Learnings: Basics Of Data, Data-driven Decisions, Data Exploration, Data Cleaning, Data Visualization, Data Analysis, Google Data Analytics Capstone Project.
Key Learnings: Data Science Basics, Tools for Data Science, Python for Data Science & Artificial Intelligence, Databases & SQL for Data Science, Data Analysis with Python, Data Visualization with Python, ML with Python.
Key Learnings: Tableau Basics, Different types of Charts, Join, Blend, Calculated Fields, Dual Axis, Data Extracts, Data Hierarchies, Dashboard, Level of Detail, Time-series, Parameters, Storylines.
Key Learnings: Display Campaigns Basics, Creating Display Ads, Placements, Exclusions, UTM parameters for Display Campaigns, Budget Management, Tracking Parameters.
Key Learnings: Search Campaigns Basics, Creating Search Ads, Conversion Tracking, UTM Tracking, Negative Search Term Reports, Keywords Analysis, Market Landing Pages.