Applied Business Analytics & Data Science

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Earners of the Applied Business Analytics & Data Science certificate understands the entire stack, from business to data science to communication. They have build a usecase from a business viewpoint, and finished a hands-on data science project in 4 weeks

Prerequisites

1. Basic Math
2. Some knowledge of Python but not compulsory
3. Analytical mindset

Goal

Most courses teach particular skills such as Algorithms and delve into great technical detail, resulting in clueless data scientists who do not comprehend the big picture. To be effective in the real world, you must understand the entire stack, from business to data science to communication. We do not follow a linear curriculum because everything is related in the real world, therefore we start with week 1 where you will design your own use case in a team, think from a business viewpoint, and finish a hands-on data science project from week 1 to week 4.

You will learn

• You will learn proven process followed in industries worldwide
• Mental Reprogramming
• Expert Mentorship

You will be able to

1. Ace interviews in the fields of data science, business analysis, and data analysis.
2. Connect a business challenge to data science.
3. You will be useful to any firm since you will be able to optimize important business indicators.
4. You can simply work and expand your expertise.

Course Outline

Week 1:
Business Metrics and Iterative Data Science Process – with Business Use case

Week 2:
Data Wrangling and Engineering with Exploratory Data Analysis – with Business Use case and real world scenarios

Week 3:
Feature Engineering – Feature Selection and Feature Extraction

Week 4:
Machine Learning 101 : Regression and Classification with mathematical depth

Week 5:
Machine Learning 201: Linear Classifier with mathematical depth and Non Linear Classifiers with Ensembles – with Business Use Case

About Saif Ali

Saif has spent a significant amount of time analyzing structured and unstructured data in order to make informed decisions. His areas of expertise include data analysis, Business Intelligence, Machine Learning, Deep Learning, and Business Data Analytics, and he is always concerned with the business outcome, which includes key indicators such as revenue, risk, and profitability.

Saif has worked on a wide range of data analytics use cases, including Churn, Segmentation, Credit Scoring for Microlending, HR Analytics, real-time campaign processing, data propensity models, Customer Journey, and many more. He has used the vast potential of machine intelligence and data analytics to boost the company's revenue.

Saif is a seasoned professional trainer and teacher who teaches machine learning all around the world and has assisted many students in achieving career success. In addition, he is the author of several data science publications.

About Training

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