Masterclass in Project Control, Planning, and Data-Driven Decision Making
$ 200
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Masterclass in Project Control, Planning, and Data-Driven Decision Making
Trainers feedback
4
(16 reviews)
Course type
Instructor led live training
Course duration
30 Hrs
Course start date & time
April 24, 2026 at 02:30 PM
Language
English
This course format is where trainer will explain you the subject via online live session. This course will run as per specific date and time.
Why enroll
Participants join this course to learn how to manage projects using modern tools like Primavera, Power BI, Python, and Power Automate. It helps them make better decisions using data, reduce manual work through automation, and improve overall project efficiency.
Course details
This course is designed to give participants a strong and practical understanding of modern project management using planning, data analysis, and automation tools. It begins with project planning and scheduling using Primavera, where learners understand how to create project timelines, allocate resources, track progress, and control delays. The course then focuses on data visualization using Power BI, helping participants convert project data into clear dashboards and reports that support better decision-making. Participants are introduced to Python and R in a simple and beginner-friendly way to analyze project data, identify trends, and predict risks. The training also covers workflow automation using Power Automate to reduce manual work, improve accuracy, and speed up project processes. Throughout the course, learners see how these tools work together in real project scenarios. Step-by-step explanations, practical examples, and real-world use cases help participants build confidence. By the end of the course, learners are equipped to manage projects more efficiently, make data-driven decisions, and use automation to improve overall project performance.
Course suitable for
Oil & Gas Energy & Utilities Pharmaceutical & Healthcare Chemical & Process Piping & Layout Onshore Pipeline Project Management
Key topics covered
Introduction to project planning and control concepts
Setting up and managing projects in Primavera
Creating Work Breakdown Structure (WBS) and activities
Scheduling techniques and resource allocation
Progress tracking and variance analysis
Reports and dashboards in Primavera
Basics of data analysis and visualizationConnecting, cleaning, and transforming data
Creating interactive dashboards and reports
Using advanced DAX functions
Real-time project monitoring
Python for data analysis (Pandas, NumPy, Matplotlib)Automating repetitive tasks using Python
R for statistical analysis and forecasting
Integrating Python and R with project tools
Basics of process automationAutomating approvals, notifications, and updates
Integration with Power BI and other tools
Real-world automation use cases in projects
Case studies integrating all toolsBest practices for project control
Troubleshooting and optimization
Hands-on project planning and executionMonitoring using dashboards and automation
Data analysis and workflow automation
Final presentation of learning outcomes
Training details
This is a live course that has a scheduled start date.
Live session
April 24, 2026 at 02:30 PM
1 Hours every day
30 Days
Our Alumni Work At
Why people choose EveryEng
Industry-aligned courses, expert training, hands-on learning, recognized certifications, and job opportunities—all in a flexible and supportive environment.
- Industry Veteran
- Trainer Review

Lummus
I love how EveryEng makes complex engineering concepts easy to understand. The platform offers valuable insights, great mentors, and a supportive community. It's truly a one-stop solution for engineers worldwide.

Siddharth Mishra
Project Manager
Frankfrut, Germany

Petrofac
I was skeptical at first, but EveryEng's training programs really delivered. I gained the skills and confidence to take on challenging projects and advance my career. Highly recommended!

Nainesh Desai
Principal Project engineer
Sharjah, UAE

ITER
The user experience on EveryEng is fantastic! The platform is simple, efficient, and provides excellent educational content. It helps developing new skills and gain confidence in engineering career.

Nirbhay Naik
Engineer
France

SaiDeepa
I’m amazed by the depth of knowledge available on EveryEng. The platform covers various engineering topics in detail, making learning both exciting and rewarding. I would highly recommend it to everyone!

Kranthi Bolineni
COO
Hydrabad, India

KPMG
From learning new technologies to getting hired, this platform changed engineer's career trajectory! It's a great work by Engineer's behind the EveryEng brain.

Rahul Dalal
Senior Resourc Manager
Dallas, USA
$ 200
April 24, 2026
Questions and Answers
A: That’s the most common mistake — blaming instrumentation when the hydraulics are lying to you. A blocked impulse line or undersized valve would show lag or failure during tests, but you said stroking and alarms are clean. Gas entrainment from a missing vortex breaker collapses the liquid head locally, so the LT reads fine while the outlet sees slugs. API sizing issues show up as chronic carryover, not episodic slugging tied to velocity spikes.
A: That’s the classic gap — assuming a gas PSV sees liquid behavior. A PSV on the vapor space won’t relieve incompressible liquid expansion when the vessel is blocked in; pressure rises too fast. Fire, valve failure, and flow transients all generate vapor-side pressure the PSV can actually see and relieve.
A: That’s where people overcorrect. Coated carbon steel fails once the coating holidays, and 316L isn’t immune to SSC in this environment. Monel works but blows the budget for no added risk reduction. Duplex hits the NACE limits with margin while keeping fabrication and inspection sane.
A: That’s the trap — treating all ‘flow’ as the same variable. The meter’s fine; the issue is mixed bases. One system is correcting to mass using live density, the other is freezing base conditions. Swirl or scan rate errors don’t land you at a clean, stable 5% offset across operating ranges.
A: That’s the blind spot — SIL math assumes independence. Two transmitters seeing the same foam don’t give you diversity; they give you synchronized bad data. Hardware random failures and power issues are already in the SIL calculation, but common process effects sail right through.
A: That’s where people confuse maximum capacity with controllability. A huge single valve hunts at normal rates, and a ball valve gives you poor resolution. An orifice just moves the problem upstream. Split-range or parallel valves let you control day-to-day while still surviving slugs.
A: That’s the geometry biting you. Raising the nozzle silently raises the hydraulic weir, shrinking the usable control band. Calibration tweaks or density changes won’t fix a physical elevation mismatch, and fail position issues show up as clear safety deviations, not oscillation.
A: That’s the subtle one — insulation changes the time-temperature curve. You might slow heat input, but you can also push the vessel into a longer-duration, high-temperature exposure where strength drops. Vapor rates don’t magically increase, and the other items aren’t fire-sizing assumptions.
A: That’s where surface metrics mislead. Raw counts and self-reported progress lag reality. When each punch is tied to a system and that system gates a milestone, trends break early and honestly, even when the numbers still look ‘fine’.
A: That’s the classic vendor-data blind spot. Internals don’t behave symmetrically across the envelope. At low velocities, vanes don’t shed liquid, so you get re-entrainment. Pressure drop, weight, and corrosion don’t selectively show up only at turndown.
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