Machine Learning Course in Washington

Extensive Program with 10 Courses View all

200+ Hours of Interactive Learning

6+ Projects and 40+ Assignments

The capstone project will provide you with a business case. You will need to solve this by applying all the skills you’ve learned in the courses of the master’s program.

Discover your full potential by attending the Machine Learning course at Washington. In this ML course, you will be taught various techniques and concepts of Machine Learning Using NLP, Python, Deep learning, and PySpark. This Machine learning course in Washington includes random forests, supervised and unsupervised learning, statistics, machine-learning algorithms, and more. Edureka's Machine learning Course in Washington offers Capstone projects, Real-time case studies, and 200+ interactive education with lifetime access for those who wish to become Machine Learning engineers.

As per Indeed.com, the average salary for a Machine Learning Engineer is $136,047 per year in United States.

You Will Learn

Python, Statistics, Data Preparation, Machine Learning, Natural Language Processing, Deep Learning, ChatGPT, Reinforcement Learning, Sequence Learning, Image Processing, Computer Vision, Spark MLlib, Data Visualization and many more skills.

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Review for Machine Learning Course in Washington

Our Masters Course Alumni work for amazing companies

Balasubramanya SP

Consultant, Deloitte US

I gained confidence to make a career leap to Data Science after this course

I had a wonderful learning experience with Edureka. Not only did I get exposed to Data Science, but I was also able to learn related technologies that helped me in my career. The course also gave me an edge over other candidates when I was looking for a job change and helped me ace my interviews. I am now planning to shift my career to Data Science and Edureka's course has given me the knowledge and confidence to make this career leap.

Machine Learning Course in Bangalore Washington

Python Statistics for Data Science Course

SELF PACED

The Python Statistics for Data Science course is designed to provide learners with a comprehensive understanding of how to perform statistical analysis and make data-driven decisions. Through a series of interactive lessons and hands-on exercises, you will learn how to conduct hypothesis testing, perform regression analysis, and many more. This course is ideal for anyone looking to enhance their data science skills and gain a deeper understanding of statistics. This course will provide you with the knowledge you need to succeed in the rapidly growing field of data science.

WEEK 3-4
6 Modules
12 Hours
6 Skills

Watch Course Recording

Python Statistics for Data Science Course

Course Content

LIVE CLASS

WEEK 4-5
11 Modules
30 Hours
11 Skills

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Course Content

Data Science with Python Certification Course

LIVE CLASS

Edureka’s Data Science with Python Certification Course, accredited by NASSCOM, is designed to help you master essential Python programming concepts for Data Science. You’ll gain expertise in data operations, file handling, object-oriented programming, and key Python libraries like Pandas, NumPy, and Matplotlib. Whether you're a beginner or a professional, this course provides a comprehensive introduction to Machine Learning, Recommendation Systems, and other critical Data Science techniques to jumpstart your career in the field.

WEEK 6-7
12 Modules
36 Hours
12 Skills

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Data Science with Python Certification Course

Course Content

Artificial Intelligence Certification Course

LIVE CLASS

Edureka's advanced AI training course is designed by industry experts to help you prepare AI Engineer, Data Scientist, NLP Engineer, etc. The objective of this Artificial Intelligence training course is to help learners improve their Computer Vision, Text Processing skills, etc. AI certification course will help you understand various concepts like OS Module, Setting the NLTK Environment, POS Tagging, etc.

WEEK 8-9
18 Modules
42 Hours
18 Skills

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Artificial Intelligence Certification Course

Course Content

ChatGPT Training Course: Beginners to Advanced

LIVE CLASS

Edureka’s ChatGPT Course will help you effectively interact with the biggest revelation in the ChatGPT. You will be able to upgrade your prompt engineering skills by integrating ChatGPT plugins and ChatGPT APIs to enhance your efficiency. Unlock your potential by crafting your very own chatbot, harnessing the knowledge gained from real-life applications and projects covered in this course, and taking a sneak peek into the future with GPT-4 and ChatGPT Plus.

WEEK 3-4
9 Modules
18 Hours
9 Skills

Watch Course Recording

ChatGPT Training Course: Beginners to Advanced

Course Content

PySpark Certification Training Course

LIVE CLASS

Edureka's PySpark certificationCourse is curated by top industry experts to help you master the skills required to become a successful PySpark developer. Gain a comprehensive understanding of the Spark stack and learn to effectively use Python in the Spark ecosystem to become a skilled PySpark developer.

WEEK 6-7
12 Modules
36 Hours
13 Skills

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Course Content

Free Elective Courses along with learning path

VIEW FREE COURSES

Self Paced

Python Scripting Certification Training

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Self Paced

Reinforcement Learning

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Self Paced

Graphical Models Certification Training

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Self Paced

Sequence Learning Certification Training

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Machine Learning Course Fee in Washington

1,499 2,533

Your total savings: 1,034

No Cost EMI Available, Starting from 167/mo.

See Course Bundle

Python Statistics for Data Science Course

119
Data Science with Python Certification Course

599
Artificial Intelligence Certification Course

449
ChatGPT Training Course: Beginners to Advanced

420
PySpark Certification Training Course

449

+4 Free Elective Courses 497

Financing options available View More

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Capstone Project

AI and Machine Learning Engineer Master Capstone Project

The objective of this project is to automatically recognize human actions based on analysis of the body landmarks from pose estimation.

Machine Learning Certification Course in Washington

Edureka’s Certificate Holders work at companies like :

John Doe

Machine Learning Engineer

Python Statistics for Data Science Course Data Science with Python Certification Course Artificial Intelligence Certification Course ChatGPT Training Course: Beginners to Advanced PySpark Certification Training Course AI and Machine Learning Engineer Master Capstone Project

XYZ1234 31st Jul 2024

The Certificate ID can be verified at www.edureka.co/verify
to check the authenticity of this certificate

Features of Machine Learning Course in Washington

As per your convenience

Weekday or weekend; morning or evening. Multiple options for everyone.

Never miss a class

You can always switch to another batch, depending upon your availability.

24x7 Support

Resolved All Your Doubts Instantly, get One-On-One Learning Assistance Round The Clock.

Lifetime Access

You'll have the keys to all our presentations, quizzes, installation guides. All for a lifetime!

Machine Learning Job Outlook

12 million Career Opportunities estimated for experienced Machine Learning Engineers in the IT industry across the globe.

Salary Trend The average salary for a Machine Learning Engineer is $136,047 per year.

22.00% Annual Growth in job opportunities for Machine Learning Engineers by 2023, worldwide.

Top Industries

Information Technology
Finance
Retail
Manufacturing
E-commerce
Media & Entertainment
Healthcare

Job Titles include

Machine Learning Engineer
Data Scientist
Artificial Intelligence (AI) Research Scientist
Computer Vision Engineer
Natural Language Processing (NLP) Engineer
Deep Learning Engineer

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Machine Learning Course in Washington FAQ's

Machine Learning Online Course FAQ

What is Artificial Intelligence?

Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks that would typically require human intelligence to complete. These tasks may include recognizing speech, making decisions, understanding natural language, recognizing images or patterns, and playing games, among others. AI involves the use of algorithms, statistical models, and computational techniques to enable machines to learn from experience, identify patterns and insights, and make decisions. AI systems may be designed to work autonomously, or they may be designed to work alongside humans to augment their capabilities and enhance their decision-making abilities. There are several subfields of AI, including machine learning, natural language processing, computer vision, robotics, and expert systems. AI has numerous applications across various industries, including healthcare, finance, transportation, and entertainment

What is Machine Learning?

Machine Learning (ML) is a subfield of Artificial Intelligence (AI) that involves the development of algorithms and statistical models that enable computer systems to learn from and make decisions based on data without being explicitly programmed. The goal of ML is to enable machines to learn from experience and improve their performance on a given task over time. ML algorithms can be trained on large datasets of examples, allowing them to identify patterns, relationships, and insights that may not be immediately apparent to human analysts. There are several types of ML algorithms, including supervised learning, unsupervised learning, and reinforcement learning. Supervised learning involves training a model on labeled data, where the correct output is known for each input. Unsupervised learning involves training a model on unlabeled data, where the algorithm must identify patterns and structures on its own. Reinforcement learning involves training a model to make decisions based on a reward system, where the algorithm learns through trial and error. ML has numerous applications across various industries, including natural language processing, computer vision, speech recognition, recommendation systems, fraud detection, and predictive maintenance, among others.

Who is a Machine Learning Engineer?

A Machine Learning Engineer is a professional who designs, develops, and maintains machine learning (ML) systems and applications. Machine learning engineers have a strong background in computer science, mathematics, and statistics and possess the technical skills needed to develop and deploy ML models.

Their primary responsibility is to build and deploy machine learning models that can learn from and make predictions on large datasets. They work with data scientists, software engineers, and other professionals to develop end-to-end ML systems that can be integrated into applications and workflows. This may involve selecting the appropriate algorithms, fine-tuning models, and deploying them in a production environment.

Machine Learning Engineers also have to keep up with the latest developments in ML and AI technologies, research and experiment with new algorithms and techniques, and continuously optimize and improve their ML models to achieve better performance.

What is Edureka’s AI and Machine Learning Course in Washington?

AI and Machine Learning Course in Washington is a structured learning path recommended by leading industry experts and ensures that you transform into a proficient Machine Learning Engineer. Being a full fledged Machine Learning Engineer requires you to master multiple technologies and this program aims at providing you an in-depth knowledge of the entire Machine Learning practices. Individual courses at Edureka focus on specialization in one or two specific skills, however, if you intend to become a master in AI and Machine Learning then this is your go to path to follow.

Why become a Machine Learning Engineer?

There are several reasons why someone may choose to become a machine learning engineer:

High Demand: There is a high demand for Machine Learning Engineers in the current job market, with many companies looking to incorporate machine learning technologies into their business processes.
Lucrative Salaries: Machine Learning Engineers are paid well, with some of the highest salaries in the tech industry.
Advancement Opportunities: Machine Learning is a rapidly growing field, and there are plenty of opportunities for career advancement and professional development.
Interesting Work: Machine Learning Engineers work on exciting projects that involve developing and implementing cutting-edge technologies, such as self-driving cars, intelligent virtual assistants, and predictive maintenance systems.
Positive Impact: Machine Learning Engineers can make a significant impact on society by developing systems that can solve complex problems and improve people's lives.
Cross-Disciplinary Skill Set: Machine Learning Engineers possess a cross-disciplinary skill set that includes computer science, mathematics, and statistics, which can be applied to a wide range of fields and industries.

Why should I enroll for the AI and Machine Learning Course in Washington?

AI and Machine Learning Course in Washington has been curated after thorough research and recommendations from industry experts. It will help you differentiate yourself with multi-platform fluency, and have real-world experience with the most important tools and platforms. Edureka will be by your side throughout the learning journey - We’re Ridiculously Committed.

What are the topics covered as a part of the AI and Machine Learning Course in Washington?

Our commitment to equip you with a 360-degree understanding of AI and Machine Learning Course in Washington means we cover a broad array of topics to ensure you become a proficient machine learning engineer. Topics covered but not limited to will be:Python, Statistics, Data Preparation, Machine Learning, Natural Language Processing, Deep Learning, Reinforcement Learning, Sequence Learning, Image Processing, Computer Vision, Spark MLlib, Data Visualization and many more skills.

What are the prerequisites for enrolling in this AI and Machine Learning Course in Washington?

There are no prerequisites for enrollment to this Masters Program. Whether you are an experienced professional working in the IT industry, or an aspirant planning to enter the world of Machine Learning, this masters program is designed and developed to accommodate various professional backgrounds.

What are the roles and responsibilities of Machine Learning Engineers?

The roles and responsibilities of machine learning engineers may vary depending on the organization, but some common tasks and responsibilities include:

Data Collection and Preprocessing: Machine Learning Engineers collect and preprocess large datasets to prepare them for analysis and modeling.
Model Selection and Design: They select appropriate models and design experiments to evaluate their performance.
Model Training and Validation: Machine Learning Engineers train and validate models using various algorithms and techniques, such as supervised and unsupervised learning.
Hyperparameter Tuning: They optimize models by tuning hyperparameters to achieve better performance.
Deployment and Integration: Machine Learning Engineers deploy models in a production environment and integrate them into applications and workflows.
Performance Monitoring: They monitor models in real-time to ensure that they are performing well and making accurate predictions.
Algorithm Development: Machine Learning Engineers develop and implement new algorithms and techniques to improve model accuracy and performance.
Collaborating with Other Teams: They collaborate with data scientists, software engineers, and other professionals to develop end-to-end ML systems.
Staying Up-to-Date with the Latest Developments: Machine Learning Engineers keep up-to-date with the latest developments in ML and AI technologies, research and experiment with new algorithms and techniques, and continuously optimize and improve their ML models.

Are the AI and Machine Learning courses Instructor-led, or Self-paced?

Edureka’s AI and Machine Learning Course in Washington is a thoughtful compilation of Instructor-led and Self-paced Training Program, allowing the learners to be guided by industry experts and learn skills at their own pace.

Who should take this AI and Machine Learning Course in Washington?

The Machine Learning Engineer training course in Washington is for those who want to fast-track their AI and Machine Learning career. This AI and Machine Learning Masters Course will benefit the people working in the following roles:

Freshers
Data Science professionals
Machine Learning professional
AI professionals
Analytics professionals
Business Analysts
Software Developers

What type of jobs opportunity will I get after completing this AI and Machine Learning Course in Washington?

On completing this Who should take this AI and Machine Learning Course in Washington, you’ll be eligible for the roles like: Machine Learning Engineer, Data Scientist, Artificial Intelligence (AI) Research Scientist, Computer Vision Engineer, Natural Language Processing (NLP) Engineer, Deep Learning Engineer, and many more.

Which are the companies hiring Machine Learning Professionals in Washington?

Top Companies Such as IBM, EMC, Amazon, GE , Honeywell, Samsung, and MuSigma are hiring Certified Machine Learning Engineer professionals at various positions.

Is this AI and Machine Learning Course in Washington suitable for freshers?

This AI and Machine Learning Course in Washington is designed to meet the requirements of both working professionals and freshers. Yes, thisWho should take this AI and Machine Learning Masters Course is suitable for freshers if you have basic knowledge of Python, Machine Learning, and Artificial Intelligence, it will be an advantage for you to follow up on our course easily. Edureka’s highly skilled trainers explain everything and make it easy to understand the concepts and resolve all your queries.

What makes Machine Learning an absolute must-know skill today?

Machine Learning has become an absolute must-know skill today due to several compelling reasons:

Increasing Demand: The demand for professionals with expertise in Machine Learning is rapidly growing across various industries.

Data Explosion: We are generating an enormous amount of data every day, and traditional methods of data analysis and decision-making are no longer sufficient.

Automation and Efficiency: Machine Learning enables automation and efficiency improvements in various domains. It can automate repetitive tasks, reduce manual effort, and improve accuracy.

Personalization and Recommendation Systems: Machine Learning algorithms drive personalized experiences and recommendation systems that we encounter every day.

Advancements in Technology: The field of Machine Learning has witnessed remarkable advancements, including more sophisticated algorithms, improved computing power, and access to vast amounts of data.

Future Relevance: Machine Learning is not just a passing trend; it is expected to play a pivotal role in shaping the future of technology and innovation.

Machine Learning has become an essential skill in today's world due to its increasing demand, ability to unlock the potential of data, automation capabilities, personalization and recommendation systems, technological advancements, and future relevance. By acquiring proficiency in Machine Learning, you open doors to exciting career prospects and contribute to solving complex problems across various industries

What is the Salary of a Machine Learning Engineer in Washington ?

The average salary for a machine learning engineer in the Washington ranged from around $100,000 to $150,000 per year. However, it's worth noting that highly skilled and experienced machine learning engineers, particularly those working at top tech companies or in specialized fields, may earn significantly higher salaries, potentially exceeding $200,000 per year.