Training Services
Brown Eagle AI Training Services
Accelerate your career in Data Science with the exclusive Data Scientist
Training program at Brown-eagle. Experience world-class Data Science
training by an industry leader on the most in-demand Data Science
and Machine learning skills. Gain hands-on exposure to key technologies
including R, Python, Tableau, Hadoop, and Spark.
Become an expert Data Scientist today.
40 hours course – Offered @ 90 Minutes per daily Session.
| Class ID | Class Name | Description |
|---|---|---|
| JB 25731 | Artificial Intelligence Class 1 Introduction to AI & Python | Artificial Intelligence (AI) Types of AI, Strong AI & Weak/Narrow AI, Major Approach, Component Of A,I Python Overview, Installing Python, Key features of Python, Python variables |
| JB 25732 | Artificial Intelligence Class 2 Key Data Structures | Data Structures & key libraries in Python, String Function, Lists, Tuples |
| JB 25733 | Artificial Intelligence Class 3 Control Flows | Loops, Conditions, Functions |
| JB 25734 | Artificial Intelligence Class 4 Numpy | ndarray basics, ndarray indexing, ndarray boolean indexing, ndarray datatypes & operations |
| JB 25735 | Artificial Intelligence Class 5 Pandas basics | Why Pandas?, data ingestion, Descriptive Statistics, Data Cleaning |
| JB 25736 | Artificial Intelligence Class 6 Matplotlib | Matplotlib basics, Basic plotting |
| JB 25737 | Artificial Intelligence Class 7 Introduction to Machine Learning | Introduction to ML, Important concepts, Unsupervised vs Supervised learning |
| JB 25738 | Artificial Intelligence Class 8 Linear Regression | Introduction, Functioning, Usage, Advantages and Disadvantages |
| JB 25739 | Artificial Intelligence Class 9 Logistic regression | Introduction, Functioning, Usage, Advantages and Disadvantages |
| JB 25740 | Artificial Intelligence Class 10 K nearest neighbour | Introduction, Functioning, Usage, Advantages and Disadvantages |
| JB 25741 | Artificial Intelligence Class 11 Decision Trees | Introduction, Functioning, Usage, Advantages and Disadvantages |
| JB 25742 | Artificial Intelligence Class 12 Support Vector Machine | What is SVM,Concepts around SVM,Case Study |
| JB 25743 | Artificial Intelligence Class 13 Random forest | Random forest |
| JB 25744 | Artificial Intelligence Class 14 K means clustering | K means clustering |
| JB 25745 | Artificial Intelligence Class 15 Hierarchical clustering | Hierarchical clustering |
| JB 25746 | Artificial Intelligence Class 16 Principal component analysis | Principal component analysis |
| JB 25747 | Artificial Intelligence Class 17 Recommendation System | What is recommendation System, How it works?, Type Finding distance, Case studies |
| JB 25748 | Artificial Intelligence Class 18 Deep learning concepts and functions | What is Deep Learning, How deep learning model work, ANN, Neural Network Architectures, Deep Learning Libraries |
| JB 25749 | Artificial Intelligence Class 19 Computer Vision Basics | Computer Vision Basics |
| JB 25750 | Artificial Intelligence Class 20 Object identification | Object identification |
| JB 25751 | Artificial Intelligence Class 21 Object Segmentation | Object Segmentation |
| JB 25752 | Artificial Intelligence Class 22 Object classification | Object classification |
| JB 25753 | Artificial Intelligence Class 23 NLP Basics | NLP Basics |
| JB 25754 | Artificial Intelligence Class 24 Text classification | Text classification |
| JB 25755 | Artificial Intelligence Class 25 Topic modeling | Topic modeling |