Course Contents

Data Science, Machine Learning and its applications
Data Visualization
Supervised and unsupervised algorithms
Analytics solutions and assessment of their effectiveness

Introduction
- Data Science
- Data Scientist
- Artificial Intelligence vs Machine Learning vs Deep Learning
- Statistical vs Machine Learning Approaches
- Big Data
- Data Life Cycle
- OSEMN - Obtain, Scrub, Explore, Model, and iNterpret
Data
- Data sources
- Obtaining the data
- Data preparation
- Identification of data requirements
- Data quality
- Duplicate, missing, and incomplete data
Exploratory Data Analysis
- Introduction
- Data Visualization
- Data Mining
- Data Wrangling
- Data Cleaning
- Data Preparation (for the model)
- Feature Engineering - Feature Scaling and Standardization
- Univariate Analysis + Multivariate Analysis + Correlation
- Descriptive statistics
- Inferences from Visualization
- Seaborn
- Matplotlib
Supervised Learning
- Supervised Learning Algorithms
- Regression
- Classification
- Logistic
- Decision Tree, Training and Visualization
- Classification And Regression Trees (CART)
- Random Forest
- Support Vector Machine
- K-Nearest Neighbour
- Case study
Model Improvement
- Association and dependence
- Differences between causation and correlation
- Simpson’s paradox
- Curse of Dimensionality (COD)
- Bias-variance trade-off
- Train-test split
- K-fold cross-validation
- Evaluation of models
- Comparison of model performance
- Computational Complexity
- Gini Impurity or Entropy
- Regularization Hyperparameters
Unsupervised Learning
- Different Clustering techniques
- K-Means Clustering
- K-Means Algorithm
- Benefits of using K-Means Clustering
- Problems & Use Cases
Industry Readiness - Project

Basic Python programming knowledge

Software options: Anaconda Navigator: https://www.anaconda.com/products/individual OR Google Colab: https://colab.research.google.com/

Instructor Profile

StepUpwards Instructor SR01

Dr. Roy is an expert in the field of Statistics, Data Science, Quality and Cyber Security with 20+ years of experience of training and teaching professionals & students in these areas. Many of his students are working in reputed companies.