Introduction to Data Science
Course Outlines
MODULE I:
FUNDAMENTAL SKILLS FOR DATASCIENCE – 20 HOURS
• Introduction to Python eco system
• Python Programing
• Python Libraries (Numpy, PANDAS, Matplotlib,
Scikit Learn)
• Linear Algebra using Python (03 Hours)
• Probability & Statistics using Python
• Data Cleaning & Wrangling using PANDAS
• Data Visualization
MODULE II:
MACHINE LEARNING TECHNIQUES
20 HOURS
• Data Preprocessing
• Supervised/Unsupervised Learning
• Linear/Logistic Regression
• Data Prediction
• ARIMA for Prediction
• Data Classification
• Support Vector Machines (SVM)
• Artificial Neural Networks (ANN)
• Convolutional Neural Networks (CNN)
• Recurrent Neural Networks (LSTM/GRU)
MODULE III:
USE CASES (APPLICATIONS)
20 HOURS
• Data Preprocessing
• Supervised/Unsupervised Learning
• Linear/Logistic Regression
• Data Prediction
• ARIMA for Prediction
• Data Classification
• Support Vector Machines (SVM)
• Artificial Neural Networks (ANN)
• Convolutional Neural Networks (CNN)
• Recurrent Neural Networks (LSTM/GRU)
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