AI ML Engineer Certification Program: Learn and Grow

The AI ML Engineer Certification Program is a game-changer for anyone looking to boost their career in the field of Artificial Intelligence and Machine Learning. This program is designed to equip you with the skills and knowledge needed to succeed in this rapidly evolving industry.

The program covers a wide range of topics, including deep learning, natural language processing, and computer vision, to name a few. You'll learn from experienced instructors and get hands-on experience with real-world projects.

With this certification, you'll have a competitive edge in the job market and be able to tackle complex projects with confidence. You'll also be part of a community of like-minded professionals who are passionate about AI and ML.

Joining this AI and ML Engineer Certification program can be a game-changer for your career. You'll receive a completion certificate from Purdue University and Simplilearn, which can be a great addition to your resume.

You'll gain industry prowess with IBM, obtaining certificates for IBM courses and accessing masterclasses by IBM experts. This can help you stay up-to-date with the latest industry developments.

One of the highlights of this program is the exposure to the latest AI trends. You'll get to attend live online classes on topics like generative AI, prompt engineering, and explainable AI, among others.

Hands-on experience is also a crucial part of this program. You'll get to work on 25+ hands-on projects and have seamless access to integrated labs with 20+ tools.

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The Program Details are quite straightforward. The AI and ML program is designed to provide a successful career in AI and ML, covering the latest advancements in the field, including ChatGPT, generative AI, and explainable AI.

You'll need to complete at least 16 days of qualifying courses, including the required Machine Learning for Big Data and Text Processing course. This can take place on MIT's campus, primarily in June, July, and August, but additional courses may be offered in other locations.

Here are the key requirements to keep in mind:

The path to success in the AI ML program is well-defined and structured. You'll start with the Program Induction, which introduces you to the principles of automation, analysis, and more. This is offered in collaboration with Purdue University, and it's a great way to begin your AI adventure.

The program is divided into several modules, each designed to build on the previous one. You'll learn about programming, data science, machine learning, and deep learning, among other topics. The curriculum is designed to equip you with the skills and knowledge to excel in your career.

Here's an overview of the learning path:

You'll also have the opportunity to attend online interactive masterclasses and live sessions delivered by industry experts. This will give you insights into the latest advancements in the AI space, including generative AI, ChatGPT, and more.

Our AI and ML program is designed to give you a solid foundation in the field, with a focus on the latest advancements such as ChatGPT, generative AI, and explainable AI.

You'll have access to a carefully curated set of modules that will take you on a journey towards a successful career in AI and ML. This program is perfect for those who want to stay at the forefront of this field.

The curriculum is structured to equip you with the skills and knowledge to excel in your career, with industry-relevant projects that will help you tackle complex challenges. Our program is designed to give you a competitive edge in the job market.

You'll learn about supervised learning, ensemble techniques, feature engineering, and model tuning through hands-on learning and AI & ML training. This will give you a solid understanding of how to apply these concepts in real-world projects.

With over 1000+ hours of training, you'll have the opportunity to explore various topics such as unsupervised learning, neural networks, natural language processing, and recommendation systems. You'll also get to work on 22+ industry-relevant projects that will help you gain practical experience.

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The admission fee for the AI and ML Course is a significant investment, but it's worth noting that it covers applicable program charges and Purdue Alumni Association membership.

The total admission fee is $4,300, which is a one-time payment.

This fee is a crucial part of securing your spot in the program, and it's essential to factor it into your budget.

By paying the admission fee, you'll also become a part of the Purdue Alumni Association, which can be a valuable resource for networking and professional development.

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The program highlights of the AI and ML program are truly impressive. You'll have the opportunity to learn from industry experts through interactive mentor-led sessions.

The program is designed to equip engineers with modern data-driven AI and ML methods, and can be completed independently or combined with other eligible certificates to create a stacked Master of Science in Artificial Intelligence and Machine Learning for Engineering.

You'll explore the fundamental applications of automation and machine learning, as well as the current capabilities and potential of generative AI. The program is structured to provide a well-rounded foundation of knowledge that can be put to immediate use.

Here are some of the program highlights:

The program allows individuals to interact with various key disciplines, including math, statistics, data analysis, computer science, and programming skills.

The capstone project is a unique opportunity to apply the knowledge gained throughout the ML/AI program to a real-world problem. You'll work with industry experts to identify a specific problem and develop a solution using the concepts, models, and tools learned in the program.

You'll have the chance to interact with professionals in your field and gain valuable insights into industry needs. This hands-on experience will help you develop a professional-quality GitHub portfolio presentation that you can share on your LinkedIn profile or with potential employers.

At the end of the program, you'll have a polished portfolio that showcases your skills and accomplishments. This is a great way to demonstrate your capabilities to potential employers and stand out in a competitive job market.

Here's a breakdown of the capstone project:

Physics-Informed Machine Learning is a required course that covers core machine learning algorithms as they apply to scientific and engineering problem solving.

This course is offered in Spring and carries 5 credits.

You'll learn how to enforce known or partially known physics into machine learning algorithms, which is a crucial skill for tackling complex scientific and engineering problems.

Physics-informed neural networks, digital twins, interpretable and generalizable models, and reinforcement learning are all topics that will be covered in this course.

You'll also work on case studies and an applied project that incorporates the skills you learn throughout the certificate program.

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The AI ML Engineer Certification program covers a wide range of skills, including Generative AI, Prompt Engineering, and Large Language Models.

You'll learn about 16+ skills in total, from ChatGPT to Computer Vision, with a focus on practical applications in engineering.

The program is designed to be completed within 36 months, with two required courses that you'll need to take first.

Here are the two required courses:

The Graduate Certificate in Artificial Intelligence and Machine Learning for Engineering is an online 18-credit graduate certificate, which includes 5-credit foundations courses, 4-credit math courses, 5-credit physics-informed machine learning courses, and 4 credits of electives.

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The Graduate Certificate in Artificial Intelligence and Machine Learning for Engineering covers a broad range of skills, including Generative AI, Prompt Engineering, and ChatGPT. These skills are essential for understanding the latest advancements in AI and ML.

The program's curriculum is designed to provide learners with a solid foundation in machine learning, including supervised and unsupervised learning, model training and optimization, and model evaluation and validation. This foundation is built on a strong understanding of probability, statistics, classification, regression, and optimization.

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Here are some of the key skills covered by the program:

These skills are essential for working in the field of AI and ML, and the program's curriculum is designed to provide learners with a comprehensive understanding of each one. By the end of the program, learners will have a solid foundation in AI and ML, and will be well-prepared to pursue a career in this exciting field.

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To implement and evaluate AI and ML methods, you need to choose the right techniques for your specific engineering application. This involves selecting from a range of methods, such as machine learning algorithms, deep learning, and natural language processing.

The goal is to find the most effective approach for your project, which may involve experimenting with different methods to see what works best. You can start by learning about the strengths and weaknesses of various AI and ML techniques.

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For instance, machine learning algorithms are great for pattern recognition and prediction, while deep learning is often used for image and speech recognition. Natural language processing is useful for text analysis and generation.

Evaluating the results of using AI and ML methods is just as important as choosing the right techniques. This involves assessing the accuracy, efficiency, and reliability of your results, as well as comparing them to other methods or benchmarks.

By following these steps, you can successfully implement and evaluate AI and ML methods in your engineering applications.

The program features of an AI ML engineer certification are quite impressive. You'll have access to Simplilearn Career Service, which helps you get noticed by top hiring companies.

The program completion certificate is issued by both Purdue University and Simplilearn, giving you credibility in the industry. You'll also gain exposure to prominent tools like ChatGPT, OpenAI, Dall-E, Midjourney, and more.

In addition to the core curriculum delivered in live classes by industry experts, you'll have the opportunity to participate in 3 capstones and 25+ hands-on projects from various industry domains. This will give you hands-on experience and a chance to build a strong portfolio.

Here are some key program features at a glance:

The Key Features of this program are truly impressive. Simplilearn Career Service helps you get noticed by top hiring companies.

This service is a game-changer for those looking to advance their careers. It's a great way to get your foot in the door with top companies.

Upon completion of the program, you'll receive a program completion certificate from Purdue University and Simplilearn. This is a fantastic way to showcase your skills and education to potential employers.

You'll also gain exposure to ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools. This is a huge plus for those looking to stay ahead in the field of AI.

The program includes live interactive sessions on the latest AI trends, such as ChatGPT, generative AI, prompt engineering, and more. These sessions are a great way to learn from industry experts and stay up-to-date on the latest developments.

Here are the Key Features of the program in a concise list:

These features are a huge part of what makes this program so valuable. By taking advantage of these resources, you'll be well on your way to success in the field of AI.

The industry projects in this program are a key part of the learning experience. You'll get to work on real-world problems using Python, data science techniques, and machine learning models.

You'll have the opportunity to develop a shopping app for an e-commerce company using Python. This project will help you apply your knowledge of automation and machine learning to a practical problem.

The program also includes a range of projects that focus on data analysis and visualization. For example, you'll use exploratory data analysis and statistical techniques to understand the factors contributing to a retail firm's customer acquisition.

Here are some of the industry projects you'll have the chance to work on:

These projects are designed to help you develop practical skills and apply your knowledge of machine learning and automation to real-world problems.

The program's focus on generative AI is a key aspect of its curriculum. Generative AI models, such as ChatGPT, are explored in depth to understand their capabilities and limitations.

You'll learn how to use generative AI models for innovative business use cases, including running small image generators or language models locally. This is a crucial skill in today's AI-driven world.

A dedicated module on generative AI fundamentals is included in the program, where you'll grasp the potential and limitations of these technologies for real-world applications. This will help you understand how to use generative AI effectively.

To take your skills to the next level, you'll learn how to integrate APIs on current platforms and analyze generative AI models for their efficacy. This will give you a solid understanding of how to deploy generative AI in real-world settings.

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Here are some key takeaways from the program's generative AI section:

By the end of the program, you'll be equipped with the skills to use cutting-edge AI tools and lead in the dynamic AI-driven world.

Data-Driven Optimization is a fundamental aspect of modern engineering, and this course covers it in depth. You'll learn optimization techniques used in machine learning and control theory.

This course covers both optimization fundamentals and deep-dives into relevant topics. You'll gain a solid understanding of convex vs. nonconvex optimization, constrained optimization, and high-dimensional and stochastic techniques for big data.

The course also covers computational techniques, which is essential for tackling complex optimization problems. By the end of the course, you'll be well-equipped to tackle data-driven optimization challenges.

This course satisfies the certificate math requirement, so you can rest assured that you're getting a solid foundation in the math behind data-driven optimization.

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