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Machine Learning Course Masters Program

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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.

Edureka's Machine Learning training course is designed by industry experts to help you prepare Machine Learning Engineer, Data Scientist, Deep Learning Engineer, etc. The objective of this Machine Learning Training course is to help learners improve their computer Vision, Spark MLlib, Data Visualization and more skills. This ML Course will help you understand various concepts like regression, mixture models, neural networks, deep learning, etc.

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.

View Curriculum

Machine Learning Course Review

Our Masters Course Alumni work for amazing companies

alumni-user-image

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 Training Syllabus

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
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Python Programming Certification Course

LIVE CLASS

The Edureka Python Training Course online is designed to help you master Python programming. It covers sequences and file operations, conditional statements, functions, loops, OOPs, modules, handling exceptions, libraries like NumPy, Pandas, and Matplotlib, GUI programming, web maps, and data operations. This course prepares you for PCEP, PCAP, and PCPP Professional Certification Exams, enabling you to kick-start your career as a certified programmer.

  • WEEK 4-5
  • 11 Modules
  • 30 Hours
  • 11 Skills
Watch Course Recording
Python Programming Certification Course
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Data Science with Python Certification Course

LIVE CLASS

Edureka's Data Science with Python Certification Course is accredited by NASSCOM. It will help you master important Python programming concepts such as data operations, file operations, object-oriented programming, and various Python libraries such as Pandas, Numpy, and Matplotlib essential for Data Science. This course is well-suited for professionals and beginners. This training will introduce you to different types of Machine Learning, Recommendation Systems, and other relevant concepts to kickstart your Data Science career.

  • WEEK 6-7
  • 12 Modules
  • 36 Hours
  • 12 Skills
Watch Course Recording
Data Science with Python Certification Course
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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
Watch Course Recording
Artificial Intelligence Certification Course
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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
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PySpark Certification Training Course

LIVE CLASS

Edureka's PySpark certification training is curated by top industry experts to help you master the skills required to become a successful PySpark developer. This certification course covers Apache Spark, Machine Learning, Spark RDD, Spark SQL, Spark MLlib, Spark Streaming, HDFS, Flume, Spark GraphX, and Kafka for building data-intensive applications.Our online training is instructor-led and enables you to master key PySpark hands-on demonstrations.

  • WEEK 6-7
  • 12 Modules
  • 36 Hours
  • 13 Skills
Watch Course Recording
PySpark Certification Training Course
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Free Elective Courses along with learning path

VIEW FREE COURSES
Self Paced

Python Scripting Certification Training

VIEW CURRICULUM
Self Paced

Reinforcement Learning

VIEW CURRICULUM
Self Paced

Graphical Models Certification Training

VIEW CURRICULUM
Self Paced

Sequence Learning Certification Training

VIEW CURRICULUM

Program Fees

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-
89,999 130,251
Your total savings: 40,252
No Cost EMI Available, Starting from 10,000/mo.
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To make this a No Cost EMI offer
The interest amount will be discounted from the price of your order. You will be charged for the item price minus the discounted interest.
See Course Bundle
  • Python Statistics for Data Science Course
    5,999
  • Python Programming Certification Course
    17,795
  • Data Science with Python Certification Course
    21,995
  • Artificial Intelligence Certification Course
    19,995
  • ChatGPT Training Course: Beginners to Advanced
    18,999
  • PySpark Certification Training Course
    21,995
+4 Free Elective Courses 23,473

Financing Options

Financing options available without any credit/debit card. The interest amount will be discounted from the price of the course and will be borne by Edureka. You will be charged the course price minus the interest.

Click on View More to avail. Conditions Apply.

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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. 

Masters Course Certification

Edureka’s Certificate Holders work at companies like :

wipro icon honeywell icon cisco icon vmware icon dell icon
certificate
John Doe
Machine Learning Engineer
Python Statistics for Data Science Course Python Programming Certification 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

AI and Machine Learning Certification Course Features

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As per your convenience

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

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Never miss a class

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

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24x7 Support

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

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Lifetime Access

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

Machine Learning Job Outlook

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

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

job-outlook-image

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

FAQs

Machine Learning Online Course FAQ

Artificial Intelligence (AI) is the simulation of human processes by machines. This includes computer systems. AI systems are created to perform tasks that require the intelligence of humans, like problem-solving and learning. They can also make decisions. These systems can analyze large amounts of information, recognize patterns, and make predictions or recommendations based on that data. 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

Machine learning is an integral component of data sciences' rapid expansion. Through statistical methods, algorithms are trained to make predictions or classifications and uncover vital insights for data mining projects, which then influence business and application decisions with positive impacts on key growth metrics. As more big data accumulates and expands exponentially, more data scientists will be needed to identify critical business questions and their answers within big data collections. 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.

Machine Learning Engineers are responsible for developing and deploying machine learning models capable of making predictions from large datasets while learning from them. Collaborating with software engineers, data scientists, and other professionals, their primary responsibility lies in designing end-to-end ML solutions integrated into applications or workflows; choosing appropriate algorithms and refining models before finally releasing them for production may also be essential responsibilities of machine Learning Engineers; they must stay abreast of new advances in AI technologies as well as experiment with new techniques to continuously optimize and improve their ML model in order to achieve excellent performance results.

AI and ML Course 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.

There are no prerequisites for enrollment in this Machine Learning Course. Whether you are an experienced IT professional or an aspirant planning to enter the world of Machine Learning certification course is designed and developed to accommodate various professional backgrounds.

The Machine learning online course with a certificate will cover topics such as regression, classification, mixture models, neural networks, deep learning, ensemble methods, and reinforcement learning.

As part of our commitment to provide you with a holistic understanding of AI and Machine Learning Course, we cover an expansive variety of topics to make you a proficient machine learning engineer. These may include Python, Statistics, Data Prep. Machine Learning, Natural Language Processing Deep Reinforcement Sequence Sequence Image Processing Computer Vision Spark MLlib Data Visualization Data Visualization among others.

Edureka is the best machine learning course for beginners and professionals. It covers basic to advanced Machine learning concepts. The course covers a broad range of topics, from basic statistical concepts and machine learning algorithms to advanced techniques like ensemble learning, recommendation systems, and natural language processing.

Machine Learning Engineers, Natural Language Processing (NLP) Engineers, and Deep Learning Engineers usually get Lucrative Salaries due to their Cross-Disciplinary Skill Sets and High Demand in various industries, including tech, healthcare, finance, and more. Machine Learning is a rapidly growing field, and there are plenty of opportunities for career advancement and professional development.

Some of the top courses are

  • Artificial Intelligence Course
  • ChatGPT Course

    • Here are some roles and responsibilities of machine learning engineers:

    • Documenting machine learning processes
    • Model evaluation
    • Scaling your data science team
    • Analyzing and improving ml algorithms
    • Designing ML systems
    • Verifying data quality

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

    Acquiring relevant certifications and skills is essential to distinguish yourself in the competitive field of machine learning. Edureka Machine Learning Certification course offers a structured path to learning about the latest trends and acquiring the necessary skills in machine learning. This course is particularly beneficial for those looking to keep pace with ongoing innovations and enhance their expertise in the field.

    Yes! You can be enrolled in multiple other Instructor-led or Self-paced courses offered by Edureka. This is the advantage of learning with us - “Flexible Schedule”. You can select the batches that allow you to make the best of your learning journey without the fear of overlapping or missing classes.

    The recommended duration to complete this AI and ML Course is 30 weeks, however, it is up to the individual to complete this course at their own pace.

    As soon as you enroll, all the 10 courses mentioned in the curriculum will be added to your account. Edureka provides its learners with immediate and lifetime access to every course, which is a part of the AI and Machine Learning Course.

    No, we do not enforce an order of course completion. Our Masters Program recommends the ideal path for becoming a Machine Learning Engineer, however, it is the learner's preference to complete the courses in any order they intend to.

    A certificate of completion for the AI and Machine Learning Course shall be awarded to you once you have completed the following courses:


    • Python Statistics for Data Science Course
    • Python Certification Training Course
    • Python Machine Learning Certification Training
    • Advanced Artificial Intelligence Course
    • ChatGPT Complete Course: Beginners to Advanced
    • PySpark Certification Training Course

    To aid your learning journey, we have added the following elective courses in the LMS:


    • Python Scripting Certification Training
    • Reinforcement Learning
    • Graphical Models Certification Training
    • Sequence Learning

    Completion of the above elective courses is not associated with Master's Program completion criteria.

    Yes, We would be providing you with the certificate of completion for every course that is a part of the learning pathway, once you have successfully submitted the final assessment and it has been verified by our subject matter experts.

    Yes, Machine Learning is an extremely promising and rapidly growing field with endless potential for professional advancement and career growth. Demand for Machine Learning professionals continues to surge as more organizations take advantage of ML to extract insights from their data and make data-driven decisions.

    Online Machine Learning course is for those who want to fast-track their AI and Machine Learning career. This AI and Machine Learning 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

    On completing this Who Should take this AI and Machine Learning Course, 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.

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

    Yes, You will get lifetime access to study materials for you should take this AI and Machine Learning Course. You can access it anytime from anywhere.

    This Machine Learning Certification Course is designed to meet the requirements of both working professionals and freshers. Yes, this Machine Learning Training 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.

    The average salary for a machine learning engineer in the United States 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.

    The Machine Learning course fee is INR 130,251, but if offers are made on the website, it can be obtained for INR 89,999. You can save up to INR 40,252. No-cost EMI is available, starting from INR10,000/mo.

    Edureka Machine Learning course is suitable for beginners and professionals. Experienced professionals curate this course to acquire basic to advanced skills.

    In machine learning, algorithms are sets of rules or procedures that enable computers to learn from data. They find patterns, make predictions, or make decisions without being explicitly programmed. Common algorithms include decision trees, neural networks, and support vector machines, each suited to different tasks. Input data, Learning process, Model creations, Testing and Validation, Optimization, etc. are the key components of Machine algortihm.

    Yes, You can download the machine learning course syllabus from the edureka platform by registering and providing your email and phone number.

    Here are the 3 steps to machine learning model training

    Step 1: For machine learning, existing data needs to be learned from, not the data our application will use.

    Step 2: Analyze data to identify patterns.

    Step 3: Make predictions.

    The four types of machine learning are:
    • Supervised Learning
    • Unsupervised Learning
    • Semi-Supervised Learning
    • Reinforcement Learning

    Best machine learning projects based on your goals, skill level, and interests, etc. Here are a few of the best projects based on different levels.

      Beginner-Level Projects:

    • Predicting House Prices (Regression)
    • Spam Email Classifier (Classification)

      • Intermediate-Level Projects:

    • Sentiment Analysis (Natural Language Processing)
    • Handwritten Digit Recognition (Image Classification)

      • Advanced-Level Projects:

    • Image Generation with GANs (Generative Models)
    • Custom Chatbots (NLP and Deep Learning)

    Preparing for a machine learning interview involves a combination of understanding theoretical concepts, practicing coding, and gaining hands-on experience with projects. Please follow these simple steps to clear your interview:

  • Strengthen Your Fundamental mathematical concepts like Linear Algebra, Probability and Statistics, Calculus and ML concepts like Supervised/Unsupervised Learning, Bias-Variance Tradeoff.
  • Master Key Algorithms and Techniques
  • Practice with Projects and Real Data
  • Get Familiar with ML Libraries
  • Understand Practical Applications
  • Brush Up on Coding Skills
  • Prepare for Common Interview Questions
  • Mock Interviews and Practice
  • Stay Updated on Industry Trends

    • These simple steps helps you to clear the ML interview easily.

    Here are some renowned books for Machine Learning for Beginners:

    • Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron
    • Machine Learning Yearning" by Andrew Ng (free)

    In the present world, Machine Learning is used in various applications like Medical Imaging and Diagnosis in the healthcare industry, Fraud Detection in Finance and Banking, Customer Segmentation in Retail and E-Commerce, Self-Driving Cars in Autonomous Vehicles, Chatbots and Virtual Assistants in NLP, Customer Churn Prediction in Marketing, etc.

    TensorFlow, Scikit-Learn, PyTorch, Keras, Apache Spark, XGBoost, LightGBM, RapidMiner, Weka, H2O.ai, etc., are the most popular Machine Learning tools.

    Data Collection, Data preprocessing, Model selection, Training, Evaluation, and Deployment. These six are Machine Learning processes.

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