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    AI and Machine Learning Masters Course

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    Course Preview
    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 AI and Machine Learning Masters Course is curated by industry experts to provide learners with a deep understanding of the principles and practices of artificial intelligence and machine learning through its extensive course work and hands-on projects. Learners will gain hands-on experience in designing and implementing model building, creating AI and machine learning solutions, performing feature engineering, working with big data, and making data-driven decisions. With our comprehensive curriculum, learners will gain the skills necessary to develop cutting-edge AI and machine learning solutions to meet the demands of any organization. Join us today and become globally recognized AI and machine learning professional!
    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

    Our Alumni

    Our Masters Course Alumni work for amazing companies

    alumni-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.

    Program 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
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    Python Certification Training Course

    LIVE CLASS

    Edureka’s Python Training Course online is created by experienced professionals to match the current industry requirements and demands. This Python Course will help you master Python programming concepts such as Sequences and File Operations, Conditional statements, Functions, Loops, OOPs, Modules and Handling Exceptions, various libraries such as NumPy, Pandas, Matplotlib, and also focuses on GUI Programming, Web Maps, Data Operations in python and more. Throughout this Python Course online, you will be working on real-time projects and this Python Course prepares you to clear PCEP, PCAP and PCPP Python Certification Professional Exams to become a certified developer.

    • WEEK 4-5
    • 11 Modules
    • 30 Hours
    • 11 Skills
    Watch Course Recording
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    Python Machine Learning Certification Training

    LIVE CLASS

    Edureka’s Machine Learning Certification Training using Python will help you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes, and Q-Learning. This Machine Learning Training will also help you understand the concepts of Statistics, Time Series, and different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. Throughout the Python Machine Learning Training, you’ll be solving real-life case studies on Media, Healthcare, Social Media, Aviation, HR.

    • WEEK 6-7
    • 12 Modules
    • 36 Hours
    • 12 Skills
    Watch Course Recording
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    Artificial Intelligence Certification Course

    LIVE CLASS

    Edureka’s Advanced Artificial Intelligence Course helps you master essentials of text processing and classifying texts along with important concepts such as Tokenization, Stemming, Lemmatization, POS tagging and many more. You will learn to perform image pre-processing, image classification, transfer learning, object detection, computer vision and also be able implement popular algorithms like CNN, RCNN, RNN, LSTM, RBM using the latest TensorFlow 2.0 package in Python. This course is curated by the industry experts after an extensive research to meet the latest industry requirements and demands. Unleash the power of Artificial Intelligence and accelerate your career— join the global revolution now!

    • WEEK 8-9
    • 18 Modules
    • 42 Hours
    • 18 Skills
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    ChatGPT-4 Complete Course: Beginners to Advanced

    LIVE CLASS

    Advance your AI knowledge and expertise with Edureka’s comprehensive ChatGPT certification training program. This comprehensive training covers the fundamentals of ChatGPT and its business use cases, as well as designing web applications, and integrating ChatGPT into your business workflows. You'll also learn about GPT models, pre-processing, fine-tuning, and working with OpenAI and the ChatGPT API and also get a sneak peek into the future with GPT-4 and ChatGPT Plus. Don't miss out on this opportunity to upskill and stand out in the digital marketplace!

    • WEEK 3-4
    • 9 Modules
    • 18 Hours
    • 9 Skills
    Watch Course Recording
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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 skills that are required to become a successful Spark developer using Python. This PySpark training will help you to master Apache Spark and the Spark ecosystem, which includes Spark RDDs, Spark SQL, Spark Streaming and Spark MLlib along with the integration of Spark with other tools such as Kafka and Flume. Our PySpark online course is live, instructor-led & helps you master key PySpark concepts with hands-on demonstrations. This PySpark training is fully immersive, where you can learn and interact with the instructor and your peers. Enroll now with this course to learn from top-rated instructors.

    • WEEK 6-7
    • 12 Modules
    • 36 Hours
    • 13 Skills
    Watch Course Recording
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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

    1,499 2,782
    Your total savings: 1,283
    No Cost EMI Available, Starting from 167/mo.
    ×
    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
      119
    • Python Certification Training Course
      349
    • Python Machine Learning Certification Training
      449
    • Artificial Intelligence Certification Course
      499
    • ChatGPT-4 Complete Course: Beginners to Advanced
      420
    • PySpark Certification Training Course
      449
    +4 Free Elective Courses 497

    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.

    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. 

    Masters Course Certification

    Edureka’s Certificate Holders work at companies like :

    certi-01
    Your Name
    Machine Learning Engineer
    Python Statistics for Data Science Course Python Certification Training Course Python Machine Learning Certification Training Artificial Intelligence Certification Course ChatGPT-4 Complete Course: Beginners to Advanced PySpark Certification Training Course AI and Machine Learning Engineer Master Capstone Project
    Sample ID NA Signature
    The Certificate ID can be verified at www.edureka.co/verify to check the authenticity of this certificate

    Program 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.

    program-feature-image
    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!

    Job Outlook

    job-outlook-image

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

    job-outlook-image

    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

    FAQ

    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

    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.

    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.

    AI and Machine Learning Masters 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 several reasons why someone may choose to become a machine learning engineer:


    1. 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.
    2. Lucrative Salaries: Machine Learning Engineers are paid well, with some of the highest salaries in the tech industry.
    3. Advancement Opportunities: Machine Learning is a rapidly growing field, and there are plenty of opportunities for career advancement and professional development.
    4. 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.
    5. 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.
    6. 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.

    AI and Machine Learning Masters Course 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.

    Our commitment to equip you with a 360-degree understanding of AI and Machine Learning Masters Course 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.

    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.

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


    1. Data Collection and Preprocessing: Machine Learning Engineers collect and preprocess large datasets to prepare them for analysis and modeling.
    2. Model Selection and Design: They select appropriate models and design experiments to evaluate their performance.
    3. Model Training and Validation: Machine Learning Engineers train and validate models using various algorithms and techniques, such as supervised and unsupervised learning.
    4. Hyperparameter Tuning: They optimize models by tuning hyperparameters to achieve better performance.
    5. Deployment and Integration: Machine Learning Engineers deploy models in a production environment and integrate them into applications and workflows.
    6. Performance Monitoring: They monitor models in real-time to ensure that they are performing well and making accurate predictions.
    7. Algorithm Development: Machine Learning Engineers develop and implement new algorithms and techniques to improve model accuracy and performance.
    8. Collaborating with Other Teams: They collaborate with data scientists, software engineers, and other professionals to develop end-to-end ML systems.
    9. 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.

    Edureka’s AI and Machine Learning Masters Course 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.

    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 Machine Learning Masters 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 Masters 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 Masters 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 a very promising and rapidly growing career field with tremendous opportunities for growth and advancement. The demand for Machine Learning professionals is continuously increasing as more and more organizations are leveraging the power of ML to gain insights from their data and make data-driven decisions.

    According to various job portals and career websites, Machine Learning is one of the top career fields in the current job market, with high-paying salaries, good job security, and exciting job roles. The field of Machine Learning is also constantly evolving and offers many exciting opportunities to work with cutting-edge technologies and solve complex real-world problems.

    Overall, if you have a passion for data science, statistics, and programming, and enjoy solving complex problems, then Machine Learning can be an excellent career choice for you.

    The Machine Learning Engineer training course 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

    On completing this Who should take this AI and Machine Learning Masters 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 of study materials for yourWho should take this AI and Machine Learning Masters Course. You can access it anytime from anywhere.

    This Who should take this AI and Machine Learning Masters Course 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.

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