Deep Learning Course (with Keras & TensorFlow) in Columbia

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Deep Learning Course Overview

The deep learning course with tensorflow training in Columbia includes the language and basic concepts of artificial neural networks, PyTorch, autoencoders, etc. Upon completion of the deep learning course with tensorflow training in Columbia, you can create a deep learning model, interpret the results, and create a learning project.

Deep Learning Course Key Features

100% Money Back Guarantee
No questions asked refund*

At Simplilearn, we value the trust of our patrons immensely. But, if you feel that this Deep Learning course does not meet your expectations, we offer a 7-day money-back guarantee. Just send us a refund request via email within 7 days of purchase and we will refund 100% of your payment, no questions asked!
  • 8X higher live interaction in live online classes by industry experts
  • Flexibility to choose classes
  • Real-life industry-based projects
  • Dedicated mentoring session from our Industry expert faculties
  • 8X higher live interaction in live online classes by industry experts
  • Real-life industry-based projects
  • Flexibility to choose classes
  • Dedicated mentoring session from our Industry expert faculties
  • 8X higher live interaction in live online classes by industry experts
  • Real-life industry-based projects
  • Flexibility to choose classes
  • Dedicated mentoring session from our Industry expert faculties

Skills Covered

  • Keras and TensorFlow Framework
  • Image Classification
  • Autoencoders
  • Conventional Neural Networks
  • ADAM Adagrad and Momentum
  • PyTorch and its elements
  • Artificial Neural Networks
  • Deep Neural Networks
  • Recurrent Neural Networks
  • Keras and TensorFlow Framework
  • PyTorch and its elements
  • Image Classification
  • Artificial Neural Networks
  • Autoencoders
  • Deep Neural Networks
  • Conventional Neural Networks
  • Recurrent Neural Networks
  • ADAM Adagrad and Momentum
  • Keras and TensorFlow Framework
  • PyTorch and its elements
  • Image Classification
  • Artificial Neural Networks
  • Autoencoders
  • Deep Neural Networks
  • Conventional Neural Networks
  • Recurrent Neural Networks
  • ADAM Adagrad and Momentum

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Get lifetime access to self-paced e-learning content

Benefits

With a deep learning course with tensorflow training in Columbia, the global deep learning system market is poised to touch a mammoth USD 93.34 billion in 2028 with a compound annual growth rate of 39.1%. With a deep learning course with tensorflow training in Columbia, one can gain skills required for the field.

  • Designation
  • Annual Salary
  • Hiring Companies
  • Annual Salary
    $83KMin
    $113KAverage
    $154KMax
    Source: Glassdoor
    Hiring Companies
    Accenture hiring for Data Scientist professionals in Columbia
    Oracle hiring for Data Scientist professionals in Columbia
    Microsoft hiring for Data Scientist professionals in Columbia
    Walmart hiring for Data Scientist professionals in Columbia
    Amazon hiring for Data Scientist professionals in Columbia
    Source: Indeed
  • Annual Salary
    $51KMin
    $72KAverage
    $110KMax
    Source: Glassdoor
    Hiring Companies
    Qualcomm hiring for AI Engineer professionals in Columbia
    Nvidia hiring for AI Engineer professionals in Columbia
    LarsenAndTurbo hiring for AI Engineer professionals in Columbia
    Honeywell hiring for AI Engineer professionals in Columbia
    Source: Indeed

Training Options

online Bootcamp

  • 90 days of flexible access to online classes
  • Lifetime access to high-quality self-paced e-learning content and live class recordings
  • 24x7 learner assistance and support
  • Cohorts starting in Columbia from:
1st Apr: Weekday Class
View all cohorts

$1,499

Corporate Training

Customised to enterprise needs

  • Blended learning delivery model (self-paced eLearning and/or instructor-led options)
  • Flexible pricing options
  • Enterprise grade Learning Management System (LMS)
  • Enterprise dashboards for individuals and teams
  • 24x7 learner assistance and support

Deep Learning Course Curriculum

Eligibility

The demand for skilled deep learning engineers in all walks of life is booming, so this deep learning course with tensorflow training in Columbia with Keras and Tensorflow certification training is very suitable for intermediate and advanced professionals. We especially recommend this deep learning course with tensorflow training in Columbia to software engineers, data scientists, data analysts and statisticians who are interested in deep learning.
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Pre-requisites

Participants of the deep learning course with tensorflow training in Columbia should be familiar with the basics of programming, have a solid understanding of the basics of statistics and mathematics, and have a firm grasp on the vital learning areas of machine learning. Candidates with this deep learning course with tensorflow training in Columbia are highly preferred by the companies for the jobs.
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Course Content

  • Section 1 - Deep Learning with Keras and Tensorflow (IBM)

    Preview
    • Lesson 01: Deep Learning with Keras and Tensorflow (IBM)

      • 1.01 Deep Learning with Keras and Tensorflow (IBM)
  • Section 2 - Deep Learning with Keras and Tensor Flow (Live Classes)

    Preview
    • Lesson 1 - Course introduction

      03:11Preview
      • Introduction
      • Accessing Practice Lab
        03:11
    • Lesson 2 - AI and Deep learning introduction

      • What is AI and Deep learning
      • Brief History of AI
      • Recap: SL, UL and RL
      • Deep learning : successes last decade
      • Demo & discussion: Self driving car object detection
      • Applications of Deep learning
      • Challenges of Deep learning
      • Demo & discussion: Sentiment analysis using LSTM
      • Fullcycle of a deep learning project
      • Key Takeaways
      • Knowledge Check
    • Lesson 3 - Artificial Neural Network

      • Biological Neuron Vs Perceptron
      • Shallow neural network
      • Training a Perceptron
      • Demo code: Perceptron ( linear classification) (Assisted)
      • Backpropagation
      • Role of Activation functions & backpropagation
      • Demo code: Backpropagation (Assisted)
      • Demo code: Activation Function (Unassisted)
      • Optimization
      • Regularization
      • Dropout layer
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project (MNIST Image Classification)
    • Lesson 4 - Deep Neural Network & Tools

      • Deep Neural Network : why and applications
      • Designing a Deep neural network
      • How to choose your loss function?
      • Tools for Deep learning models
      • Keras and its Elements
      • Demo Code: Build a deep learning model using Keras (Assisted)
      • Tensorflow and Its ecosystem
      • Demo Code: Build a deep learning model using Tensorflow (Assisted)
      • TFlearn
      • Pytorch and its elements
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Build a deep learning model using Pytorch with Cifar10 dataset
    • Lesson 5 - Deep Neural Net optimization, tuning, interpretability

      • Optimization algorithms
      • SGD, Momentum, NAG, Adagrad, Adadelta , RMSprop, Adam
      • Batch normalization
      • Demo Code: Batch Normalization (Assisted)
      • Exploding and vanishing gradients
      • Hyperparameter tuning
      • Interpretability
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Hyperparameter Tunning With Keras Tuner
    • Lesson 6 - Convolutional Neural Network

      • Success and history
      • CNN Network design and architecture
      • Demo code: CNN Image Classification (Assisted)
      • Deep convolutional models
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Image Classification
    • Lesson 7 - Recurrent Neural Networks

      • Sequence data
      • Sense of time
      • RNN introduction
      • LSTM ( retail sales dataset kaggle)
      • Demo code: Stock Price Prediction with LSTM (Assisted)
      • Demo code: Multiclass Classification using LSTM (Unassisted)
      • Demo code: Sentiment Analysis using LSTM (Assisted)
      • GRUs
      • LSTM Vs GRUs
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Stock Price Forecasting
    • Lesson 8 - Autoencoders

      • Introduction to Autoencoders
      • Applications of Autoencoders
      • Autoencoder for anomaly detection
      • Demo code: Autoencoder model for MNIST data (Assisted)
      • Key Takeaways
      • Knowledge Check
      • Lesson-end Project: Anomaly detection with Keras
  • Section 3 - Practice Projects

    Preview
    • Practice Projects

      • PUBG Players Finishing Placement Prediction
  • Free Course
  • Math Refresher

    Preview
    • Lesson 01: Course Introduction

      06:23Preview
      • 1.01 About Simplilearn
        00:28
      • 1.02 Introduction to Mathematics
        01:18
      • 1.03 Types of Mathematics
        02:39
      • 1.04 Applications of Math in Data Industry
        01:17
      • 1.05 Learning Path
        00:25
      • 1.06 Course Components
        00:16
    • Lesson 02: Probability and Statistics

      32:38Preview
      • 2.01 Learning Objectives
        00:29
      • 2.02 Basics of Statistics and Probability
        03:08
      • 2.03 Introduction to Descriptive Statistics
        02:12
      • 2.04 Measures of Central Tendencies​
        04:50
      • 2.05 Measures of Asymmetry
        02:24
      • 2.06 Measures of Variability​
        04:55
      • 2.07 Measures of Relationship​
        05:22
      • 2.08 Introduction to Probability
        08:36
      • 2.09 Key Takeaways
        00:42
      • 2.10 Knowledge check
    • Lesson 03: Coordinate Geometry

      06:31
      • 2.01 Learning Objectives
        00:29
      • 2.02 Basics of Statistics and Probability
        03:08
      • 2.03 Introduction to Descriptive Statistics
        02:12
      • 2.04 Measures of Central Tendencies​
        04:50
      • 2.05 Measures of Asymmetry
        02:24
      • 2.06 Measures of Variability​
        04:55
      • 2.07 Measures of Relationship​
        05:22
      • 2.08 Introduction to Probability
        08:36
      • 2.09 Key Takeaways
        00:42
      • 2.10 Knowledge check
    • Lesson 04: Linear Algebra

      29:53Preview
      • 4.01 Learning Objectives
        00:29
      • 4.02 Introduction to Linear Algebra
        03:21
      • 4.03 Forms of Linear Equation
        05:21
      • 4.04 Solving a Linear Equation
        05:21
      • 4.05 Introduction to Matrices
        02:05
      • 4.06 Matrix Operations
        07:07
      • 4.07 Introduction to Vectors
        01:00
      • 4.08 Types and Properties of Vectors
        01:52
      • 4.09 Vector Operations
        02:39
      • 4.10 Key Takeaways
        00:38
      • 4.11 Knowledge Check
    • Lesson 05: Eigenvalues Eigenvectors and Eigendecomposition

      08:56Preview
      • 5.01 Learning Objectives
        00:29
      • 5.02 Eigenvalues
        01:19
      • 5.03 Eigenvectors
        04:09
      • 5.04 Eigendecomposition
        02:21
      • 5.05 Key Takeaways
        00:38
      • 5.06 Knowledge Check
    • Lesson 06: Introduction to Calculus

      09:47Preview
      • 6.01 Learning Objectives
        00:30
      • 6.02 Basics of Calculus
        01:20
      • 6.03 Differential Calculus
        03:01
      • 6.04 Differential Formulas
        01:01
      • 6.05 Integral Calculus
        02:33
      • 6.06 Integration Formulas
        00:47
      • 6.07 Key Takeaways
        00:35
      • 6.08 Knowledge Check

Project

  • Project 1

    PUBG Players Finishing Placement Prediction

    Create a model that predicts players’ finishing placement based on their final stats, on a scale of 1 (first place) to 0 (last place).

  • Project 2

    Lending Club Loan Data Analysis

    Create a model that predicts whether a loan will go into default using the historical data.

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TensorFlow Exam & Certification

Deep Learning Certificate in Columbia
  • Who provides the certification and how long is it valid for?

    Once you complete of the deep learning course with tensorflow training in Columbia successfully, you will be awarded an industry-recognized course completion certificate from Simplilearn has lifelong validity. The deep learning course with tensorflow training in Columbia will help you to fetch a well-paid job.

  • What do I need to do to unlock my Simplilearn certificate?

    To obtain a deep learning course with tensorflow training in Columbia, you will need to:
    Attend one complete batch of this deep learning course with tensorflow training in Columbia.
    Finish and acquire an evaluation for atleast one of the projects mentioned below;. 
    After the completion of the course, you will be given a certification of a deep learning course with tensorflow training in Columbia.

  • What is the fee for the TensorFlow Developer certification exam?

    The deep learning course with tensorflow training in Columbia exam costs $100, which includes one exam attempt. The deep learning course with tensorflow training in Columbia will help you to expand your knowledge in this particular subject. 

  • What is the duration of the TensorFlow Developer certification exam?

    After you start the deep learning course with tensorflow training in Columbia, you have 5 hours to complete and submit it. However, if you do not submit a response within 5 hours, the portal will automatically send your response for the deep learning course with tensorflow training in Columbia after that time.

  • How many attempts do I have to pass the TensorFlow Developer certification exam?

    For the deep learning course with tensorflow training in Columbia, you will have three attempts to pass the deep learning course with tensorflow course in Columbia exam.  For the deep learning course with tensorflow course in Columbia, there are no more attempts you can try.

  • What are the system requirements for taking the TensorFlow Developer certification exam?

    To be able to appear for the deep learning course with tensorflow training in Columbia examination, here are the minimum requirements that you need to have:

    • RAM - 4 GB
    • Disk Space - 2.5 GB and another 1 GB for caches
    • Monitor resolution - 1024 x 768
    • Operating system - officially released 64-bit versions of
    • macOS 10.13 or subsequent upgrades, Microsoft Windows 8 or future versions, or any Linux distribution supporting tools including Gnome, KDE, or Unity DE.
    • These are the minimum requirements for the deep learning course with tensorflow training in Columbia examination

  • What are the benefits of taking the TensorFlow Developer certification exam?

    Here are the benefits of taking the deep learning course with tensorflow training in Columbia:

    • Learn new things about Machine Learning - This deep learning course with tensorflow training in Columbia exam will help you increase your proficiency in Machine Learning.
    • Receive recognition - Once you are certified, it is imperative that you will be recognized by the TensorFlow community.
    • Showcase skills - The deep learning course with tensorflow training in Columbia is internationally recognized and attests to the knowledge that you possess and as an extension also is proof of the skills you’ve practiced and perfected with this course.
    • The deep learning course with tensorflow training in Columbia also helps one to build their passion for this subject.

  • How do I crack the Tensorflow Developer certification exam?

    The best way to pass the deep learning course with tensorflow training in Columbia exam is to take this deep learning course with tensorflow training in Columbia. After completing the deep learning course with tensorflow training in Columbia, you will be able to register and take the TensorFlow developer certification exam. There will be five categories during the exam, and students will complete five models, one for each category. These categories include basic ML models, models from learning data sets, CNNs with real image data sets, NLP text classification with real text data sets, and sequence models with real numerical data sets. This exam can be taken on a system that supports the requirements of PyCharm IDE.

Deep Learning Training Reviews

  • A.Anthony Davis

    A.Anthony Davis

    Kingston

    The Simplilearn Data Scientist Master’s Program is an awesome course! You learn how to solve real-world problems, and the wide variety of projects give you hands-on experience to make you industry-ready. The lecturers are experts and share their knowledge energetically. Thank you for an excellent learning experience.

  • Abhishek Tripathi

    Abhishek Tripathi

    Bangalore

    Good online content for data science. I completed Data Science with R and Python. The instructors have good knowledge on the subject. Self-learning videos help a lot, too. Thanks, Simplilearn.

  • Angiras Modak

    Angiras Modak

    Associate System Engineer at IBM India Pvt. Ltd., Kolkata

    Simplilearn is one of the best online training providers available. The trainer was really great in explaining the concepts to the minute detail and also gave multiple real-world examples. The course content was very informative. I understood the concept of CNN. Overall I really enjoyed the training a lot.

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Why Online Bootcamp

  • Develop skills for real career growthCutting-edge curriculum designed in guidance with industry and academia to develop job-ready skills
  • Learn from experts active in their field, not out-of-touch trainersLeading practitioners who bring current best practices and case studies to sessions that fit into your work schedule.
  • Learn by working on real-world problemsCapstone projects involving real world data sets with virtual labs for hands-on learning
  • Structured guidance ensuring learning never stops24x7 Learning support from mentors and a community of like-minded peers to resolve any conceptual doubts

Deep Learning Training FAQs

  • What is Deep Learning?

    Deep Learning, also known as Deep Neural Learning, is a subset of machine learning, an application of AI, where machines imitate the workings of the human brain and employ artificial neural networks to process the information.

  • What is TensorFlow?

    TensorFlow is an open source library created and released by google for numerical computation and building deep learning models.

  • Why should I learn Deep Learning?

    In traditional machine learning, most of the applied features need to be identified by a domain expert in order to reduce the complexity of the data. Whereas the biggest advantage of the Deep Learning algorithm is it tries to learn high-level features from data in an incremental manner, which makes the process simpler and popular. Deep Learning techniques outperform other techniques when the data size is large and complex, and also, this technique is behind many high-end innovations.

  • How do I become a Deep Learning Engineer?

    This Deep Learning with Keras and TensorFlow certification course in Columbia will give you a complete overview of  Deep Learning concepts, enough to prepare you to excel in your next role as a Deep Learning Engineer. It will help you become familiar with artificial neural networks, PyTorch, autoencoders, and more. At the end of the course, you will get an industry-recognized course completion certificate from Simplilearn, which will be a testament to your skills.

  • What is the salary of a Deep Learning Engineer in Columbia?

    A Machine Learning Engineer in Colombia earns an average yearly income of COL$90 million. Skills in Machine Learning, Python, and Artificial Intelligence (AI) have all been related to greater pay. Salary disparities vary depending on the amount of experience one has in a certain area. A deep learning course with tensorflow training Columbia provides students with the chance to work on real-world projects.

  • What are the major companies hiring for Deep Learning Engineers in Columbia?

    AI and Machine Learning professionals, as well as AI and Machine Learning training, are in great demand in Columbia. Pearson and Tata Consultancy Services are some of the companies that are looking for Machine Learning Engineers. You might be able to get there by taking a deep learning course with tensorflow training Columbia.

  • What are the major companies hiring for Deep Learning Engineers in Columbia?

    AI and Machine Learning professionals, as well as AI and Machine Learning training, are in great demand in Columbia. Pearson and Tata Consultancy Services are some of the companies that are looking for Machine Learning Engineers. You might be able to get there by taking a deep learning course with tensorflow training Columbia.

  • What are the major companies hiring for Deep Learning Engineers in Columbia?

    AI and Machine Learning professionals, as well as AI and Machine Learning training, are in great demand in Columbia. Pearson and Tata Consultancy Services are some of the companies that are looking for Machine Learning Engineers. You might be able to get there by taking a deep learning course with tensorflow training Columbia.

  • What are the major industries in Columbia?

    Columbia's most notable industries included manufacturing, healthcare, insurance information technology, and a variety of others. In Columbia's main industries, AI and machine learning specialists come highly recommended. A deep learning course with tensorflow training Columbia might help you get there.

  • How to become a Deep Learning Engineer in Columbia?

    AI is the research and development of computer systems that can do tasks that were previously confined to human intelligence, such as decision-making and voice recognition. Machine Learning is a subfield of artificial intelligence that investigates how to train computers to learn and adapt without being explicitly programmed.

  • How to become a Deep Learning Engineer in Columbia?

    AI is the research and development of computer systems that can do tasks that were previously confined to human intelligence, such as decision-making and voice recognition. Machine Learning is a subfield of artificial intelligence that investigates how to train computers to learn and adapt without being explicitly programmed.

  • How to Find Deep Learning Courses in Columbia?

    Anyone with great interest and desire for new-age digital talents is welcome to enroll in the deep learning courses with tensorflow instruction in Columbia. You must, however, have a bachelor's degree with at least a 50 percent grade point average. A basic grasp of programming languages and mathematics, on the other hand, is useful.

  • Why is Deep Learning important?

    Companies are gathering a massive amount of data every day and analyzing them to draw meaningful business insights. Most of that data is in an unstructured format, i.e. in the form of text, image, audio, and video rather than numerical. Deep learning is quite effective for analyzing such types of data and has become vitally important for business decision making. With our Deep Learning Training with TensorFlow & Keras certification, you can learn all the essential deep learning concepts from scratch.

  • What kind of careers can I pursue with a background in Deep Learning?

    With the relevant skills that you gain from our Deep Learning course, you can apply for top job roles like Machine Learning Engineer, Data Scientist, Business Intelligence Developer, NLP Scientist, and more.

  • Why should you take this Deep Learning course?

    Deep learning skills are in high demand and offer professionals a clear edge over others when applying for top related job roles like Machine Learning Engineer, Data Scientist, or NLP Specialist. Requiring a high level of technical understanding, one may not find it easy to learn deep learning through self-study. Taking up this Deep Learning course is a better option where you get the right guidance from industry experts.

  • What is online classroom training?

    All of the TensorFlow training classes are conducted via live online streaming. These classes for the TensorFlow course are interactive sessions that enable you to ask questions and participate in discussions during class time.

  • Who are the instructors and how are they selected?

    All of our highly qualified trainers are Deep Learning and Machine Learning industry experts with years of relevant industry experience. Each of them has gone through a rigorous selection process that includes profile screening, technical evaluation, and a training demo before they are certified to train for us. We also ensure that only those trainers with a high alumni rating remain on our faculty.

  • How will the labs be conducted?

    Simplilearn provides Integrated labs for all the hands-on execution of projects. The learners will be guided on all aspects, from deploying tools to executing hands-on exercises.

  • What is Global Teaching Assistance?

    Our teaching assistants are a dedicated team of subject matter experts here to help you get certified in TensorFlow in your first attempt. They engage students proactively to ensure the Deep Learning Course path is being followed and help you enrich your learning experience, from class onboarding to project mentoring and job assistance. Teaching Assistance is available during business hours.  

  • Is this live training or will I watch pre-recorded videos?

    The TensorFlow certification training is conducted through live streaming. They are interactive sessions that enable you to ask questions and participate in discussions during class time. We do, however, provide recordings of each TensorFlow course session you attend for your future reference. Classes are attended by a global audience to enrich your learning experience.

  • What if I miss a class?

    Simplilearn provides recordings of each class of Deep Learning course so you can review them as needed before the next session. With Flexi-pass, Simplilearn gives you access to all classes for 90 days so that you have the flexibility to choose sessions as per your convenience.

  • What is covered under the 24/7 Support promise?

    We offer 24/7 support through email, chat, and calls. We also have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after completion of your Deep Learning course online with us.

  • How do I enroll for the Deep Learning course?

    You can enroll for this Deep Learning Training on our website and make an online payment using any of the following options: 

    • Visa Credit or Debit Card
    • MasterCard
    • American Express
    • Diner’s Club
    • PayPal

    Once payment is received you will automatically receive a payment receipt and access information via email.

  • If I need to cancel my enrollment, can I get a refund?

    Yes, you can cancel your enrollment if necessary. We will refund the Deep Learning course price after deducting an administration fee. To learn more, please read our Refund Policy.

  • How can I learn more about this Deep Learning course?

    Contact us using the form on the right of any page on the Simplilearn website, or select the Live Chat link. Our customer service representatives can provide you with more details.

Deep Learning Course (with Keras & TensorFlow) in Columbia

Columbia is the world's second most biodiverse country, with 51,464,958 residents as of July 30, 2021. It is a city in the United States of America. The Columbia is 361.7 km2 in size and rises to a height of 89 metres. In 2020, Colombia's gross domestic product is anticipated to be about 271.46 billion dollars.

In 2020, Colombia's real gross domestic product will be revised down by 6.85 percent from the previous year. Oil, mining, agriculture, and industry are the cornerstones of its market economy.

Throughout the year, the temperature in the Republic of Columbia fluctuates from 36°F to 92°F, with lows of 23°F and highs of 98°F being rare. Columbia gets 38 inches of rain on average each year.

Columbia is known for its biodiversity as well as its rich cultural history and legacy. The following are some of Columbia's tourist attractions:

  • Columbia Canal and Riverfront Park
  • Columbia Museum Of Art
  • EdVenture Children’s Museum
  • Sesquicentennial State Park
  • Saluda Shoals Park

  • Disclaimer
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.