Data Science and Machine Learning: Making Data-Driven Decisions
5.0 /5- Offered byGreat Learning
Data Science and Machine Learning: Making Data-Driven Decisions at Great Learning Overview
Duration | 12 weeks |
Total fee | ₹1.60 Lakh |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Go to Website  |
Credential | Certificate |
Data Science and Machine Learning: Making Data-Driven Decisions at Great Learning Highlights
- Earn a certificate from the MIT Schwarzman College of Computing
- Fee can be paid in instalments
- 3 industry-relevant hands-on projects and 50+ real-world case studies
- Personalized mentorship and support
- Learn from renowned MIT Faculty
Data Science and Machine Learning: Making Data-Driven Decisions at Great Learning Course details
Data scientists, data analysts, and professionals who wish to turn large volumes of data into actionable insights
Those with some academic/ professional training in applied mathematics/ statistics. Participants without this experience will have to put in extra work and will be provided support by Great Learning
Course encompass the most business-relevant technologies, such as Machine Learning, Deep Learning, NLP, Recommendation Systems, and more
This course will provide participants with the skills & knowledge to apply data science techniques to help you make data-driven decisions
Participants will construct their understanding through solving real-world case studies and practice activities
The Data Science and Machine Learning Program curriculum has been carefully crafted by MIT faculty to provide you with the skills & knowledge to apply data science techniques to help you make data-driven decisions
It encompass the most business-relevant technologies, such as Machine Learning, Deep Learning, NLP, Recommendation Systems, ChatGPT, Generative AI and more
Data Science and Machine Learning: Making Data-Driven Decisions at Great Learning Curriculum
Foundations - Python and Statistics
Python for Data Science
Statistics for Data Science
Project 1
Making Sense of Unstructured Data
Introduction
Clustering
Spectral Clustering, Components, and Embeddings
Regression and Prediction
Classical Linear and Nonlinear Regression and Extensions
Modern Regression with High-Dimensional Data
The Use of Modern Regression for Causal Inference
Classification and Hypothesis Testing
Hypothesis Testing and Classification
Project 2
Deep Learning
Deep Learning
Recommendation Systems
Recommendations and Ranking
Collaborative Filtering
Personalized Recommendations
Networking and Graphical Models
Introduction
Networks
Graphical Models
Predictive Analytics
Predictive Modeling for Temporal Data
Feature Engineering
Data Science and Machine Learning: Making Data-Driven Decisions at Great Learning Faculty details
Other courses offered by Great Learning
Data Science and Machine Learning: Making Data-Driven Decisions at Great Learning Students Ratings & Reviews
6 Ratings- 4-56
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