No Code Analytics and AI offered by MIT University
- Private University
168 acre campus- Estd. 1861
No Code Analytics and AI at MIT University Overview
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 at MIT University Course details
- 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
- 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
- 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 University 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
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No Code Analytics and AI at MIT University Contact Information
77 Massachusetts Ave, Cambridge, MA 02139, USA
Cambridge ( Massachusetts)