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Course Content

Total learning: 14 lessons Time: 10 weeks
  • 1. Exploratory Data Analytics (EDA) / Descriptive Analytics  0/1

  • 2. Statistical Data Business Intelligence and Data Visualization  0/1

  • 3. Plots & Inferential Statistics  0/1

  • 4. Probability Distributions (Continuous & Discrete)  0/1

  • 5. Hypothesis Testing - The ‘4’ Must Know Hypothesis Tests  0/1

  • 6. CRISP – DM - Project Management Methodology  0/1

  • 7.Supervised Learning – Linear Regression  0/1

  • 8. Predictive Modelling – Multiple Linear Regression  0/1

  • 9. Lasso and Ridge Regressions  0/1

  • 10. Logistic Regression – Binary Value Prediction, MLE  0/1

  • 11. Multinomial Regression  0/4

  • 12. Advanced Regression for Count Data  0/0

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  • 13. Machine Learning - k -NN Classifier  0/0

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  • 14. Decision Tree & Random Forest  0/0

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  • 15. Ensemble Techniques - Bagging and Boosting  0/0

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  • 16. AdaBoost & Extreme Gradient Boosting  0/0

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  • 17. Text Mining and Natural Language Processing (NLP)  0/0

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  • 18. Machine Learning Classifier Technique - Naive Bayes  0/0

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  • 19. Introduction to Perceptron and Multilayer Perceptron  0/0

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  • 20. Building Blocks of Neural Network - ANN  0/0

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  • 21. Deep Learning Primer  0/0

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  • 22. Kernel Method - SVM  0/0

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  • 23. Data Mining Unsupervised Learning – Clustering  0/0

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  • 24. Data Mining Unsupervised Learning - Dimension Reduction (PCA)  0/0

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  • 25. Data Mining Unsupervised Learning - Association Rules  0/0

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  • 26. Recommendation Engine  0/0

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  • 27. Network Analytics  0/0

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  • 28. Auto Machine Learning (Auto ML)  0/0

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  • 29. Survival Analytics  0/0

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  • 30. Forecasting/Time Series – Model-Driven Algorithms  0/0

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  • 31. Forecasting/Time Series - Data-Driven Algorithms  0/0

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  • 32. Introduction to Artificial Intelligence and Deep learning  0/0

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  • 33. Introduction to P32. Introduction to Artificial Intelligence and Deep learningython Libraries  0/0

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  • 34. Machine Learning Primer  0/0

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  • 35. Mathematical Foundations  0/0

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  • 36. Deep Learning Primer  0/0

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  • 37. Perceptron Algorithm and Back Propagation Neural Network Algorithm  0/0

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  • 38. Artificial Neural Network (ANN), Multilayer Perceptron (MLP)  0/0

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  • 39. Convolution Neural Networks - CNN  0/0

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  • 40. Image Processing and Computer Vision  0/0

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  • 41. Recurrent Neural Network - RNN  0/0

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  • 42. CNN + RNN Variants, Fast R-CNN and Mask R-CNN  0/0

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  • 43. Long Short Term Memory - LSTM  0/0

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  • 44. Gates Recurrent Units - GRUs  0/0

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  • 45. Autoencoders, Variational Autoencoders, RBM  0/0

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  • 46. Deep Belief Networks (DBNs)  0/0

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  • 47. Generative Adversarial Networks - GAN  0/0

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  • 48. Super Resolution GAN  0/0

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  • 49. Reinforcement Learning and Q-learning  0/0

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  • 50. Speech Recognition  0/0

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  • 51. Automatic Text Generation and Chatbot  0/0

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  • 52. Auto Artificial intelligence (Auto AI)  0/0

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  • 53. Explainable Artificial Intelligence (XAI)  0/0

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₹49,999

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