Training Mode | Regular | Fastrack | Crash |
---|---|---|---|
Classroom | Online | 6 Months (M,W,F or T,T,S Class) (3 Class in a week) |
4 Months (Monday to Friday Class) (5 Class in a week) |
2 Months (Monday to Friday Class) (5 Class in a week 1:30 hour duration) |
Introduction :
1. Getting Started with ARTIFICIAL INTELLIGENCE
2. An Introduction to ARTIFICIAL INTELLIGENCE
3. What is ARTIFICIAL INTELLIGENCE ?
4. Introduction to Data in ARTIFICIAL INTELLIGENCE
5. Demystifying ARTIFICIAL INTELLIGENCE
6. ML – Applications
7. Best Python libraries for ARTIFICIAL INTELLIGENCE
8. Artificial Intelligence | An Introduction
9. ARTIFICIAL INTELLIGENCE and Artificial Intelligence
10. Difference between ARTIFICIAL INTELLIGENCE and Artificial Intelligence
11. Agents in Artificial Intelligence
12. 10 Basic ARTIFICIAL INTELLIGENCE Interview Questions
Data and It’s Processing:
1. Introduction to Data in ARTIFICIAL INTELLIGENCE
2. Understanding Data Processing
3. Python | Create Test DataSets using Sklearn
4. Python | Generate test datasets for ARTIFICIAL INTELLIGENCE
5. Python | Data Preprocessing in Python
6. Data Cleansing
7. Feature Scaling – Part 1
8. Feature Scaling – Part 2
9. Python | Label Encoding of datasets
10. Python | One Hot Encoding of datasets
11. Handling Imbalanced Data with SMOTE and Near Miss
Name : Manish Bharti
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Guided By : Rajesh Sir
Name : Manish Bharti
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