Learn the fundamentals of procedural and object-oriented programming with Python. Discover Python’s key benefits, how to install it, and set up its IDE. Master Jupyter Notebook for hands-on development. Explore core programming concepts such as identifiers, indentation, comments, data types, operators, and string functions. Understand control structures, variable scopes, and the principles of OOP including methods, attributes, and access control.

Begin your journey into data science with IBM’s Python-centric course. Learn programming basics in the context of data science, building a strong foundation in Python that supports further AI and ML learning.

• Learn essential Python tools and libraries used in data science

• Develop practical, job-ready skills through real-world applications

• Engage in a blended learning experience combining theory and hands-on practice

• Strengthen your understanding with practical data science use cases

• Advance your career with Simplilearn’s specialized training path

• Master core machine learning concepts through 40+ hours of applied learning

• Participate in interactive labs and complete four hands-on projects

• Get personalized mentoring support throughout your journey

• Gain the skills and certification required to become a machine learning engineer

Understand how deep learning differs from traditional ML. Study various neural network architectures and learn forward/backward propagation. Dive into model tuning, interpretability, dropout, early stopping, CNNs, object detection, and RNNs. Get hands-on with PyTorch to build and train neural networks.

Put your skills to the test by solving real-world industry problems. Use a variety of AI and ML techniques to build a final project that demonstrates your expertise to future employers.

Enhance your ML toolkit by mastering deep learning using Keras and TensorFlow. Learn to build neural networks, apply abstraction layers, and utilize data more effectively to fuel AI advancements.

Dive deep into computer vision with a focus on practical applications. Learn image formation, CNNs, object detection, segmentation, OCR, and generative models. Explore distributed computing, explainable AI (XAI), and advanced model deployment techniques.

Explore how to apply machine learning to large-scale text data. Learn key NLP techniques driving innovation in the AI space and develop the skills needed to pursue a career as an NLP Engineer.

Get hands-on experience with reinforcement learning techniques using Python. Understand agent-environment interaction, reward systems, and policy optimization through practical applications.

Explore advanced concepts in generative modeling, including transformers, VAEs, GANs, and autoencoders. Learn when and how to apply each model, understand attention mechanisms, and compare architectures like GPT and BERT for different generative AI use cases.

Join live sessions conducted by industry leaders to gain insights into the latest advancements in AI. Topics include Generative AI applications, building GPT-based products, understanding ChatGPT architecture, and real-world use cases. (Topics are subject to change based on industry trends.)

Develop predictive models to estimate sales and demand across 45 retail stores, factoring in holidays, promotions, and economic indicators to reduce stockouts and enhance forecasting accuracy.

Build machine learning models to forecast employee attrition. This includes data quality checks, exploratory data analysis (EDA), clustering, and recommending retention strategies based on predictive scoring.

Apply exploratory data analysis and clustering techniques to categorize songs into meaningful groups based on common patterns and features.

Leverage deep learning to analyze historical loan data and build a model that predicts the likelihood of future loan defaults, helping financial institutions manage risk effectively.

Earn industry-recognized credentials from IBM and Nvidya, validating your expertise in AI. Key program benefits include:

• Masterclasses led by IBM experts
• Interactive Ask-Me-Anything (AMA) sessions with IBM leadership
• Participation in IBM-conducted hackathons
• IBM certification for completing IBM-led courses

Nvidya program completion certificate recognized by the industry

This program prepares you for a variety of high-demand roles in the AI and data science ecosystem, such as:

• Artificial Intelligence Engineer
• Machine Learning Engineer
• Data Scientist
• Analytics Manager or Lead
• Statistical Programming Specialist

Get continuous support throughout your learning journey via email, chat, phone, and community forums. Once you complete the program, you'll enjoy lifetime access to the community forum for peer interaction, mentorship, and ongoing learning.

A Master’s in Artificial Intelligence is a comprehensive training program designed to help learners gain foundational and advanced knowledge in AI. This program equips you with job-ready AI skills and focuses on developing and applying AI technologies. You’ll dive deep into key topics such as:
• Generative AI fundamentals
• Programming essentials
• Natural Language Processing (NLP)
• Deep Learning techniques
• Reinforcement Learning

 

An AI Engineer builds intelligent systems that solve real-world problems. They design, develop, and deploy AI models and algorithms, using tools like machine learning, neural networks, and data analytics. AI Engineers also collaborate with teams across domains to integrate AI solutions into existing platforms and systems.

 

Nvidya's AI Master's instructors are seasoned professionals with hands-on industry experience. They are selected through a rigorous vetting process based on expertise, teaching ability, and certifications in AI and ML. These experts bring real-world insights to enrich your learning.

You can enroll in the Master’s in AI by:
• Filling out the online application form via the "Enroll Now" button.
• Making a secure payment through credit/debit cards (Visa, MasterCard, AmEx, Diners Club) or PayPal.
• Receiving course access and a payment receipt via email once the payment is completed.

 

Absolutely. This program offers:
• A deeper understanding of current AI practices and trends
• Industry-relevant, job-ready skills
• Expertise in ML, NLP, computer vision, and neural networks
• Globally recognized certifications from Nvidya and IBM
• Opportunities to build a strong network and grow your career

 

Salaries vary based on experience, location, and industry. On average:
• In the U.S., AI Engineers earn around $137,000 per year (source: Payscale).
• In India, the average annual salary is approximately INR 12 LPA (source: AmbitionBox).

After graduating, you can explore roles such as:
• AI Engineer
• Machine Learning Engineer
• Data Scientist
• NLP Specialist
These roles are in demand across sectors like BFSI, IT services, consulting, manufacturing, and more. With leadership and problem-solving skills, you can also transition into managerial positions.

 

We provide:
• 24/7 live chat support for urgent queries
• Email and callback assistance from our dedicated support team

 

No, coding is not a strict prerequisite. However, basic programming knowledge is recommended as it can help you grasp the material more easily.

 

To excel in AI, you need a blend of technical and analytical skills:
Technical Skills:
• Python or R programming
• Mathematical foundations (statistics, linear algebra)
• Understanding of ML, NLP, computer vision, etc.
Analytical Skills:
• Ability to interpret data
• Critical thinking for algorithm evaluation
• Creative problem-solving

 

Yes. The program is beginner-friendly and suitable for professionals from non-CS backgrounds. A foundational understanding of math (especially statistics and algebra) will be helpful, but the course builds AI knowledge from scratch.

 

Yes! AI is booming, with growing applications across industries like healthcare, automotive, and finance. It offers:
• High demand and excellent salary prospects
• Opportunities to work on cutting-edge tech
• Continuous learning and professional growth
• A strong professional network

 

The challenge level depends on your background, but Nvidya’s program is designed for accessibility. While prior experience in programming and math is helpful, the course covers all fundamental concepts in a structured manner to ease learning.

 

Yes, a bachelor’s degree is required. A background in computer science, engineering, or math is beneficial, though not mandatory.

 

This AI Master’s, created with IBM, offers:
• Certifications from Nvidya and IBM
• Live expert-led classes and masterclasses
• Hands-on practice in integrated labs
• Lifetime access to self-paced learning
• JobAssist for career support
• Exposure to tools like Python, NLP, ML, ChatGPT, and more

 

No worries. You can catch up through our Flexi-Learn feature, which allows access to recorded sessions so you stay on track.

Yes. Nvidya for Business delivers tailored learning paths and certifications in AI and emerging technologies. Our Learning Hub+ also provides unlimited access to interactive training for entire teams.

We also offer:
• Applied AI Course
• Machine Learning using Python
• Introduction to AI
• Advanced Postgraduate Programs
These options allow you to deepen your expertise beyond the Master’s program.

The program is highly rated for its:
• Expert-led curriculum
• Flexibility
• Real-world projects
• Collaboration with IBM
Learners appreciate the job-ready training and industry-recognized certifications.

 

You must have a bachelor's degree in a relevant field. While AI knowledge is preferred, it’s not required. No prior work experience is necessary.