Overview
Course Outline
Introduction
Python for Data Science
Introduction to Python
Python installation & configuration
Python Features
Basic Python Syntax with implementation
Statements, Indentation, and Comments
Data Analytics using R
Introduction to R
RStudio installation & configuration
Basic Python Syntax
Basic visualization and data analysis
Statistics and Mathematics for Machine Learning
Statistical Inference
Descriptive Statistics
Introduction to Probability, Conditional probability, Bayes theorem
Probability Distribution
Introduction to inferential statistics
Normality, Normal Distribution
Measures of Central Tendencies
Hypothesis Testing
Data visualization using python
Machine Learning in Python
Machine Learning introduction
Machine Learning applications & use-cases
Machine Learning Flow
Machine Learning categories
Exploratory data analysis
Data cleaning and Imputation Techniques
Linear regression
Gradient descent
Model evaluation
Supervised Learning
What is Supervised Learning?
Logistic Regression in Python
Classification & implementations
Decision Tree
Different algorithms for Decision Tree Induction
How to create a Perfect Decision Tree
Confusion Matrix
Random Forest
Tree based Ensemble
Hyper-parameter tuning
Evaluating model output
Naive Bayes Classifier
Support Vector Machine
Unsupervised Learning
What is Unsupervised Learning
Clustering
K-means Clustering
Hierarchical Clustering
Data Mining
Association Rules
Recommendation Engines
Organizational Competencies for Deployment – This module will guide you through the organizational Competencies for deployment. Learn to Apply systems thinking to anticipate the effect that components of a system can have and execute Leadership Roles. Support functioning of Master Black Belts through plans. Learn about the organizational performance metrics.
Organizational Design
Executive and Team
Organizational Challenges
Organizational Change Management
Organizational Feedback
Organizational Performance Metrics
Project Portfolio Management – Learn about Project Portfolio Management in this module. Evaluate critical projects and apply phases of project management life cycle. Learn to create document tracking tools and more. Execute positioning of multiple projects and measure the performance
Project Management Principles and Life Cycle
Project Portfolio Infrastructure and Management
Project Portfolio Financial Tools
Training Design and Delivery – This module will guide you through various training design and delivery methodologies. Discover training requirements by using tools as a gap analysis & design training plans. Learn to outsource training methods and monitor the training effectiveness
Training Needs Analysis
Training Plan Elements
Training Materials and Curriculum Development
Training Program Effectiveness
Coaching and Mentoring Responsibilities – Learn about the various Coaching and mentoring responsibilities in this module. Candidates will use coaching, mentoring and intervention skills to create a career progression ladder for belts. Learn to create guidelines for project reviews
Executives and Champions
Teams and Individuals
Advanced Data Management and Analytic Methods – This module will equip you with the knowledge of advanced data management and analytic methods. Learn about the measurement Systems analysis, Process capability, and more. Gain skills and knowledge of Design of experiments and data management and analytics
Measurement Systems Analysis (MSA), Process Capability, and Control
Measuring and Modelling Relationships Between Variables
Design of Experiments (DOE)
Data Management and Analytics
DFSS (Design for Six Sigma)
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