Description

Data Science, Analytics & AI for Business & the Real World™ 2020

This is a practical course, the course I wish I had when I first started learning Data Science.

It focuses on understanding all the basic theory and programming skills required as a Data Scientist, but the best part is that it features  35+ Practical Case Studies covering so many common business problems faced by Data Scientists in the real world.

Right now, even in spite of the Covid-19 economic contraction, traditional businesses are hiring Data Scientists in droves!

And they expect new hires to have the ability to apply Data Science solutions to solve their problems. Data Scientists who can do this will prove to be one of the most valuable assets in business over the next few decades!

“Data Scientist has become the top job in the US for the last 4 years running!” according to Harvard Business Review & Glassdoor.

However, Data Science has a difficult learning curve – How does one even get started in this industry awash with mystique, confusion, impossible-looking mathematics, and code? Even if you get your feet wet, applying your newfound Data Science knowledge to a real-world problem is even more confusing.

This course seeks to fill all those gaps in knowledge that scare off beginners and simultaneously apply your knowledge of Data Science and Deep Learning to real-world business problems.

This course has a comprehensive syllabus that tackles all the major components of Data Science knowledge.

Our Complete 2020 Data Science Learning path includes:

   Using Data Science to Solve Common Business Problems
   The Modern Tools of a Data Scientist – Python, Pandas, Scikit-learn, NumPy, Keras, prophet, statsmod, scipy and more!
   Statistics for Data Science in Detail – Sampling, Distributions, Normal Distribution, Descriptive Statistics, Correlation and Covariance, Probability Significance Testing, and Hypothesis Testing.
   Visualization Theory for Data Science and Analytics using Seaborn, Matplotlib & Plotly (Manipulate Data and Create Information Captivating Visualizations and Plots).
   Dashboard Design using Google Data Studio
   Machine Learning Theory – Linear Regressions, Logistic Regressions, Decision Trees, Random Forests, KNN, SVMs, Model Assessment, Outlier Detection, ROC & AUC and Regularization
   Deep Learning Theory and Tools – TensorFlow 2.0 and Keras (Neural Nets, CNNs, RNNs & LSTMs)
   Solving problems using Predictive Modeling, Classification, and Deep Learning
   Data Analysis and Statistical Case Studies – Solve and analyze real-world problems and datasets.
   Data Science in Marketing – Modeling Engagement Rates and perform A/B Testing
   Data Science in Retail – Customer Segmentation, Lifetime Value, and Customer/Product Analytics
   Unsupervised Learning – K-Means Clustering, PCA, t-SNE, Agglomerative Hierarchical, Mean Shift, DBSCAN and E-M GMM Clustering
   Recommendation Systems – Collaborative Filtering and Content-based filtering + Learn to use LiteFM  + Deep Learning Recommendation Systems
   Natural Language Processing – Bag of Words, Lemmatizing/Stemming, TF-IDF Vectorizer, and Word2Vec
   Big Data with PySpark – Challenges in Big Data, Hadoop, MapReduce, Spark, PySpark, RDD, Transformations, Actions, Lineage Graphs & Jobs, Data Cleaning and Manipulation, Machine Learning in PySpark (MLLib)
   Deployment to the Cloud using Heroku to build a Machine Learning API

Our fun and engaging Case Studies include:

Sixteen (16) Statistical and Data Analysis Case Studies:

   Predicting the US 2020 Election using multiple Polling Datasets
   Predicting Diabetes Cases from Health Data
   Market Basket Analysis using the Apriori Algorithm
   Predicting the Football/Soccer World Cup
   Covid Analysis and Creating Amazing Flourish Visualisations (Barchart Race)
   Analyzing Olympic Data
   Is Home Advantage Real in Soccer or Basketball?
   IPL Cricket Data Analysis
   Streaming Services (Netflix, Hulu, Disney Plus and Amazon Prime) – Movie Analysis
   Pizza Restaurant Analysis – Most Popular Pizzas across the US
   Micro Brewery and Pub Analysis
   Supply Chain Analysis
   Indian Election Analysis
   Africa Economic Crisis Analysis

Six (6) Predictive Modeling & Classifiers Case Studies:

   Figuring Out Which Employees May Quit (Retention Analysis)
   Figuring Out Which Customers May Leave (Churn Analysis)
   Who do we target for Donations?
   Predicting Insurance Premiums
   Predicting Airbnb Prices
   Detecting Credit Card Fraud

Four (4) Data Science in Marketing Case Studies:

   Analyzing Conversion Rates of Marketing Campaigns
   Predicting Engagement – What drives ad performance?
   A/B Testing (Optimizing Ads)
   Who are Your Best Customers? & Customer Lifetime Values (CLV)

Four (4) Retail Data Science Case Studies:

   Product Analytics (Exploratory Data Analysis Techniques
   Clustering Customer Data from Travel Agency
   Product Recommendation Systems – Ecommerce Store Items
   Movie Recommendation System using LiteFM

Two (2) Time-Series Forecasting Case Studies:

   Sales Forecasting for a Store
   Stock Trading using Re-Enforcement Learning
   Brent Oil Price Forecasting

Three (3) Natural Langauge Processing (NLP) Case Studies:

   Summarizing Reviews
   Detecting Sentiment in text
   Spam Detection

One (1) PySpark Big  Data Case Studies:

   News Headline Classification

One (1) Deployment Project:

   Deploying your Machine Learning Model to the Cloud using Flask & Heroku

Who this course is for:

   Beginners to Data Science
   Business Analysts who wish to do more with their data
   College graduates who lack real world experience
   Business oriented persons (Management or MBAs) who’d like to use data to enhance their business
   Software Developers or Engineers who’d like to start learning Data Science
   Anyone looking to become more employable as a Data Scientist
   Anyone with an interest in using Data to Solve Real World Problems

Requirements

   No need to be a programming or math whiz, basic highschool math would be sufficient
   All programming is taught in this course making it beginner friendly

Last Updated 11/2020