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)