Program Overview

The No Code AI and Machine Learning: Building Data Science Solutions program is designed to equip learners with industry-valued AI and Machine Learning skills through an industry-relevant curriculum. The program is led by MIT faculty and includes in-depth modules on Generative AI, Responsible AI, and Agentic AI.

Program Details

• Duration: 12 weeks
• Format: Online
• Tuition Fee: $2,850 USD
• Certificate: Certificate of Completion from MIT Professional Education upon successful completion of the program

Program Outcomes

The program aims to enable learners to:

• Transform data into actionable insights using intuitive, no-code platforms
• Rapidly prototype, test, and operationalize machine learning models without writing code
• Leverage supervised and unsupervised learning, recommendation systems, deep learning, and computer vision
• Utilize Generative AI, Prompt Engineering, and Agentic AI to design intelligent, autonomous workflows

Curriculum

The industry-relevant curriculum includes modules covering:

• Pre-work: Introduction to Data Science and AI
• Week 1: Introduction to the AI and Generative AI Landscape
• Week 2: Data Exploration - Structured Data
• Week 3: Prediction Methods – Regression
• Week 4: Decision Systems
• Week 5: Project Week - Machine Learning Classification
• Week 6: Recommendation Systems
• Week 7: Prediction Methods – Neural Networks
• Week 8: Computer Vision Methods
• Week 9: Project Week - Neural Networks
• Week 10: Generative AI Foundations
• Week 11: Business Applications of Generative AI
• Week 12: Ethical and Responsible AI
• Self-Paced Modules: Data Exploration: Unstructured Data, Data Exploration: Temporal Data

Projects and Case Studies

The program includes 3 hands-on projects and over 20 case studies across various industries, such as:

• Hospitality
• Marketing and Advertising
• EdTech
• Healthcare
• Food & Nutrition Tech
• E-commerce

No-Code Tools Covered

• KNIME
• RapidMiner
• Teachable Machine
• ChatGPT
• Gemini
• NotebookLM
• Dall E
• And More...

Program Faculty

The program is led by MIT faculty, including:

• Stefanie Jegelka
• Caroline Uhler
• John N. Tsitsiklis
• Munther Dahleh
• Devavrat Shah

Learner Reviews

Learners have praised the program for its comprehensive curriculum, expert faculty, and supportive program managers.

Application Process

To apply, complete the online application form. The Great Learning program team will review your submission to assess your fit for the program.

Frequently Asked Questions

• What is the required weekly time commitment? The program consists of 10 modules, totaling approximately 80 study hours. Most participants can expect to spend an average of 6 to 12 hours per week on program activities.
• Is the program completely virtual? Yes, the program is delivered entirely online, allowing you to learn from anywhere.
• Will I receive a transcript or grade after completion of the program? No, the No Code AI and Machine Learning Program is a non-degree online program offered by MIT Professional Education in collaboration with Great Learning. As it is not a full-time or credit-bearing university program, official grades or transcripts are not issued. However, participants receive performance marks for each assessment and module to evaluate their understanding and determine eligibility for the certificate.

Massachusetts Institute of Technology (MIT)

---

Overview:

The Massachusetts Institute of Technology (MIT) is a renowned private research university located in Cambridge, Massachusetts. It is widely recognized for its exceptional academic programs, groundbreaking research, and strong emphasis on innovation. MIT is consistently ranked among the top universities globally, attracting students and faculty from diverse backgrounds.

---

Services Offered:

---

Student Life and Campus Experience:

MIT offers a vibrant and intellectually stimulating campus experience. Students have access to a wide range of resources and opportunities, including:

Research:

Students can engage in research alongside renowned faculty, contributing to cutting-edge discoveries.

Clubs and Organizations:

A diverse array of clubs and organizations cater to various interests, fostering a sense of community and providing opportunities for leadership development.

Athletics:

MIT boasts a strong athletic program, with competitive teams in various sports.

Campus Events:

The campus hosts numerous events, lectures, and performances, enriching the academic and cultural experience.

---

Key Reasons to Study There:

World-Class Faculty:

MIT attracts some of the world's leading researchers and educators, providing students with access to exceptional mentorship and guidance.

Innovative Curriculum:

The curriculum emphasizes hands-on learning, problem-solving, and interdisciplinary approaches, preparing students for future success.

Global Impact:

MIT graduates make significant contributions to various fields, driving innovation and addressing global challenges.

Strong Alumni Network:

The MIT alumni network is vast and influential, providing valuable connections and support throughout students' careers.

---

Academic Programs:

MIT offers a wide range of undergraduate and graduate programs across various disciplines, including:

Engineering:

MIT is renowned for its engineering programs, particularly in fields like aerospace, computer science, and mechanical engineering.

Science:

The university excels in scientific research, with strong programs in biology, chemistry, physics, and mathematics.

Management:

MIT's Sloan School of Management is highly regarded for its business programs, including MBA and master's degrees.

Humanities and Social Sciences:

MIT also offers programs in the humanities and social sciences, fostering critical thinking and interdisciplinary perspectives.

---

Other:

MIT is committed to fostering a diverse and inclusive community, welcoming students from all backgrounds. The university also emphasizes sustainability and environmental responsibility, promoting research and initiatives in these areas.