Course Curriculum
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Module 1
In this Module we will cover, Introduction to AI and Machine Learning. Application of Machine Learning- Supervised, Unsupervised and Reinforcement Learning, Classification, Regression, Clustering, Anomaly Detection Recommendation, System Algorithms in Machine Learning and Introduction to Deep Learning
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Module 2
In this module you will be able to popup with Python Programming, Object of this Module to make a fearless Python Coder, You will get to learn, practices and implement use cases, Build expertise in python programming, after learning python you can quick start with AI & ML
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Module 3
In this module you will experience different tools for Statistics-
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Module 4
In this module you will learn about Statistics of Data- Data Variable, Mean, Mode, Median, Standard Deviation Variance, Correlation and Probability
- Session 9. Descriptive Statistics, Inferential Statistics, Variable, Median, Percentile, RFM
- Session 10. Variance, Standard Deviation and IQR, Chebyshev’s Theorem
- Session 11. Covariance, Correlation, Kurtosis, Skewness, Analyzing the Continuous and Categorical Data, Probability
- Session 12. Chi-Square Test & Prediction
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Module 5
Starting with Machine Learning Algorithms
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Module 6
In this module we will starting with Artificial Neural NetWorks
- Session 20. Possibility the survival of passenger in titanic- Model, Random Forest and Introduction to Artificial Neural Networks
- Session 21. Artificial Neural Networks, Architecture and Mathematical Modelling of Neural Network
- Session 22. Backpropagation algorithm
- Session 23. Backpropagation algorithm-Model
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Module 7
Here, are continue with ANN Example and Introduction with Image Processing
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Module 8
Here you are going to learn forecasting, time series
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Module 9
Here you will learn Unsupervised learning
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Module 10
In this module you will learn Natural Language Processing and It's Model