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PMP Lecture 6 Collect Requirements and Define Scope

Introduction to PMP HOW and WHAT of Project Management Professional

PMP Lecture 1 PMP Certification requirements and Course Content

PMP Lecture 1 PMP Certification requirements and Course Content

PMP Lecture 2 Project Management Framework

PMP Lecture 3 part 1 Project Management Life Cycle

PMP Lecture 3 part 2 Project Management Process Groups

PMP Lecture 4 part 1 Integration Management

PMP Lecture 4 part 2 Integration Management

PMP Lecture 5 Plan Scope Management

PMP Lecture 6 Collect Requirements and Define Scope

PMP Lecture 7 Create Work Breakdown Structure WBS

PMP Lecture 8 Validate Project Scope and Control Scope

PMP Lecture 9 Plan Schedule Management and Define Activities

PMP Lecture 10 Sequence Activities

PMP Lecture 11 part 1 Estimate Activity Duration

PMP Lecture 11 part 2 Estimate Activity Duration

PMP lecture 12 part 1 Develop Schedule Critical Path

PMP Lecture 12 part 2 Develop Schedule Schedule Compression

PMP Lecture 12 part 3 Develop Schedule Control Schedule

PMP Lecture 13 Plan Cost Management

PMP Lecture 14 Estimate Cost

PMP Lecture 15 Determine Budget

PMP Lecture 16 Control Cost

PMP Lecture 17 Understanding Earned Value Management EVM

PMP Lecture 18 Introduction to Quality Management

PMP Lecture 19 Plan Quality Management

PMP Lecture 20 Manage Quality in project

PMP Lecture 21 Project Control Quality

PMP Lecture 22 Plan Resource Management

PMP Lecture 23 Estimate Activity Resources

PMP Leature 24 Acquire Resources

PMP Lecture 25 How to Develop a Team

PMP Lecture 26 Managing Teams

PMP Lecture 27 Control Resources

PMP Lecture 28 Plan Communications Management

PMP Lecture 29 Manage Communications

PMP Lecture 30 Monitor Communications

PMP Lecture 32 Identify Risks

PMP Lecture 31 Plan Risk Management

PMP Lecture 33 Perform Qualitative Risk Analysis

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Linear Algebra for Computer Scientists

Insertion Sort

Bubble Sort

GCSE Computer Science

Random Access Memory

Binary Trees

Bitwise Operators

Data Structures and Algorithms

Organization Theory Structure and Design

Handling Large Scale Unit Level Data Using STATA

Introduction to Machine Learning

Applied Linear Algebra Vectors Matrices and Least Squares

Artificial Intelligence Principles and Techniques

Machine Learning

Robotics and Autonomous Systems

Natural Language Understanding