Data Science & Deep Learning for Business™ 20 Case Studies

November 26, 2019 Data Science, Development, Udemy CoursesUdemy

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Data Science & Deep Learning for Business™ 20 Case Studies

Use Python for Data Analysis, Data Science in Marketing & Retail, Recommendations, Forecasts, Customer Clustering & NLP

Created by Rajeev Ratan | 16 hours on-demand video course

Welcome to the course on Data Science & Deep Learning for Business™ 20 Case Studies! This course takes on Machine Learning and Statistical theory and teaches you to use it in solving 20 real-world Business problems. Data Scientist is the buzz of the 21st century for good reason! The tech revolution is just starting and Data Science is at the forefront. As a result, “Data Scientist has become the top job in the US for the last 4 years running!” according to Harvard Business Review & Glassdoor.

What you’ll learn

Understand the value of data for businesses
Learn to use Python, Pandas, Matplotlib & Seaborn, SkLearn, Keras, Tensorflow, NLTK, Prophet, PySpark, MLLib and more!
Apply Data Science in Marketing to improve Conversion Rates, Predict Engagement and Customer Life Time Value
Machine Learning from Linear Regressions (polynomial & multivariate), K-NNs, Logistic Regressions, SVMs, Decision Trees & Random Forests
Unsupervised Machine Learning with K-Means, Mean-Shift, DBSCAN, EM with GMMs, PCA and t-SNE
Build a Product Recommendation Tool using collaborative & item/content based
Hypothesis Testing and A/B Testing – Understand t-tests and p values
Natural Langauge Processing – Summarize Reviews, Sentiment Analysis on Airline Tweets & Spam Detection
To use Google Colab’s iPython notebooks for fast, relaible cloud based data science work
Deploy your Machine Learning Models on the cloud using AWS
Advanced Pandas techniques from Vectorizing to Parallel Processsng
Statistical Theory, Probability Theory, Distributions, Exploratory Data Analysis
Predicting Employee Churn, Insurance Premiums, Airbnb prices, credit card fraud and who to target for donations
Big Data skills using PySpark for Data Manipulation and Machine Learning
Cluster customers based on Exploratory Data Analysis, then using K-Means to detect customer segments
Build a Stock Trading Bot using re-inforement learning
Apply Data Science & Analytics to Retail, performing segementation, analyzing trends, determining valuable customers and more!