No Code Analytics and AI
offered by MIT USA

Private University
168 acre campus
Estd. 1861

No Code Analytics and AI
at
MIT USA
Overview

Discover how the no-code tool eco-system can be used to democratize data science in organizations

Duration	4 days
Total fee	₹1.95 Lakh
Mode of learning	Online
Schedule type	Self paced
Course Level	UG Certificate

No Code Analytics and AI

Table of content

Overview
Course Details
Curriculum
Faculty

No Code Analytics and AI
at
MIT USA
Course details

Skills you will learn

Data mining Statistics Communication skills Data Science Forecasting

Who should do this course?

For Managers who need to make data-driven decisions that drive teams and projects forward
For Domain Experts
For Business Analysts
For Strategy or Finance Manager/Directors
For VPs of Marketing or Operations
For IT Directors
For Data Engineers/DB Analysts
For Software Development Engineers

What are the course deliverables?

Understand the core concepts of data science and explain how they apply to real world challenges
Examine the primary principles underlining descriptive, predictive, and prescriptive analytics
Enhance your ability to explore and understand your organization?s unique data
Learn how to build machine learning models to make predictions
Translate analytic outputs into feasible and actionable changes within an organization

More about this course

In this course, you will acquire the no-code analytics and AI tools you need to become a ?citizen data scientist??a professional who is equipped to perform analytical tasks while working in an area of expertise outside statistics and analytics
This knowledge will negate the need for hundreds of lines of code and enable you to focus on contextualizing questions and communicating the results to drive positive change
The tools also provide a platform to bring together managers, domain experts, and data scientists
Alongside a group of global peers, you will master key data science concepts and learn frameworks for translating organizational challenges into data science questions without code

No Code Analytics and AI
at
MIT USA
Curriculum

Day One

Democratizing data science: Challenges and opportunities

Descriptive analytics: How to prepare and explore your data

Data exploration lab

Day Two

Predictive analytics, model key outcomes

ML model lab

Forecasting: Working with time series data

Forecasting lab

Day Three

Process and event data and feature engineering

Process mining and modeling lab

Prescriptive analytics: Techniques for data-driven decision making

Deploying models and data products

Day Four

Deploying models and data products

Data product lab

No-code tool ecosystem

Strategies to democratize data science within an organization

Closing remarks

No Code Analytics and AI
at
MIT USA
Faculty details

Tim Kraska

Tim Kraska is an Associate Professor of Electrical Engineering and Computer Science in MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), where he co-leads the Data Systems Group. He is also the Founding Co-Director of MIT Data System and AI Lab (DSAIL).