Certified in Data Science
Total Number of Modules6
Total Number of Topics135
Estimated Duration420:30 H
Module 1 – Data Science Overview
- Introduction to Data Science90 Mins
Module 2 – Python
- Python Setup, Environment and Basics120 Mins
- Practice Program45 Mins
- Python Operators90 Mins
- Practice Program40 Mins
- Python Control Statements180 Mins
- Practice Program60 Mins
- Python Loops240 Mins
- Practice Program90 Mins
- List and Set210 Mins
- Practice Program45 Mins
- Tuple & Dictionary210 Mins
- Practice Program60 Mins
- Function210 Mins
- Practice Program120 Mins
- Python Modules120 Mins
- Practice Program90 Mins
- Assessment120 Mins
- Python Oops - Class & Object120 Mins
- Practice Program90 Mins
- Python Oops - Inheritance & Polymorphism180 Mins
- Python Oops - Abstraction & Encapsulation180 Mins
- Practice Program120 Mins
- Python File & Exception Handling150 Mins
- Practice Program210 Mins
Module 3 – Exploratory Data Analysis (EDA)
- Introduction to NumPy60 Mins
- NumPy Arrays90 Mins
- Array Indexing and Slicing60 Mins
- NumPy Operations60 Mins
- Array Manipulation60 Mins
- NumPy Linear Algebra120 Mins
- NumPy Random Module60 Mins
- NumPy Data Handling90 Mins
- Practice Questions30 Mins
- Introduction to Pandas30 Mins
- Creating and Accessing Data30 Mins
- Selecting and Modifying Data30 Mins
- Data Aggregation and Grouping30 Mins
- Advanced Data Handling60 Mins
- Practice Program30 Mins
- Introduction to Statistics180 Mins
- Data Visualization60 Mins
- Matplotlib60 Mins
- Seaborn60 Mins
- Practice Program120 Mins
- Assessment60 Mins
- Main Project (Stock Market / Covid-19 Analysis)180 Mins
Module 4 – Machine Learning
- Introduction of Machine Learning120 Mins
- Data Preprocessing120 Mins
- Probability120 Mins
- Hypothesis Testing120 Mins
- Bayes' Theorem90 Mins
- Sampling Techniques90 Mins
- Central Limit Theorem (CLT)60 Mins
- Statistical Decision Making: p-value Method60 Mins
- Feature Selection60 Mins
- Feature Extraction & Train_Test_Split90 Mins
- Introduction of Supervised Learning120 Mins
- Regression120 Mins
- Classification180 Mins
- Assessment120 Mins
- Supervised Learning - Project 1250 Mins
- Introduction of Unsupervised Learning60 Mins
- Clustering60 Mins
- Dimensionality Reduction90 Mins
- Assessment160 Mins
- Unsupervised Learning - Project 2210 Mins
- Reinforcement Learning180 Mins
- Assessment180 Mins
- Reinforcement Learning - Project 3180 Mins
- Assessment30 Mins
Module 5 – Streamlit
- Introduction to Streamlit90 Mins
- User Inputs90 Mins
- Streamlit with Machine Learning90 Mins
- Assessment30 Mins
- Streamlit Project - Diabetes Prediction90 Mins
Module 6 – Deep Learning
- Introduction to Deep Learning90 Mins
- Neural Networks90 Mins
- How Deep Learning Works120 Mins
- Deep Learning Life Cycle90 Mins
- Deep Learning Models (ANN, CNN, RNN, GAN, LSTM, Autoencoder)240 Mins
- MCQ Test60 Mins
- Assessment30 Mins
- Main Project (Cancer Prediction / Digit Generator / Autoencoders)240 Mins
Module 7 – MySQL
- Fundamentals of MySQL60 Mins
- Practice Program60 Mins
- Querying & Filtering Data60 Mins
- Practice Program60 Mins
- Joins & Relational Queries60 Mins
- Practice Program60 Mins
- MySQL Connectivity Basics30 Mins
- Advanced MySQL Connectivity60 Mins
- Assessment60 Mins
- Project - Employee–Department Management System120 Mins