UG Certification in AI Data Engineering
This programme is offered by TheSSML in collaboration with the Continuing Technology and Interprofessional Education (CTIPE).
About the Programme
The UG Certification in AI Data Engineering is a comprehensive 24 Months program designed to equip undergraduate students with the knowledge and skills necessary to work with data in AI and machine learning applications. The program covers a wide range of topics including data collection, preprocessing, storage, and management, as well as the integration of data systems for AI model training and deployment. Students will learn how to build and optimize data pipelines, ensuring that data is prepared and structured effectively for use in AI algorithms.
Throughout the program, students will gain hands-on experience with tools and technologies used in data engineering, such as databases, cloud platforms, and big data technologies, as well as AI-specific tools for data analysis. The curriculum emphasizes real-world problem solving, and students will apply their knowledge in practical projects and assignments, simulating industry scenarios.
By the end of the program, students will have developed a strong foundation in data engineering principles tailored for AI applications, making them well-prepared for careers as Data Engineers, AI Engineers, and Machine Learning Specialists. The program also includes placement support, helping graduates transition into the workforce.
Key Skills Developed
Who is the programme for?
The UG Certification in AI Data Engineering is ideal for undergraduate students who are interested in data science, artificial intelligence, and machine learning, and want to specialize in data engineering. This program is designed for students who aspire to build and manage data pipelines, optimize data workflows, and support the development of AI models. It is suitable for those with a basic understanding of programming and mathematics, and who are keen to pursue careers in data-driven technologies. Whether you're looking to work as a data engineer, AI engineer, or machine learning specialist, this program provides the foundational knowledge and hands-on experience required for success in the rapidly evolving field of AI and data engineering.
How will you study?
The UG Certification in AI Data Engineering utilizes a blend of theoretical learning and practical experience to ensure a well-rounded education. You will study through the following methods:
- Live Online Classes: Interactive sessions led by experts in AI and data engineering, providing real-time insights and opportunities for questions and discussion.
- Pre-recorded Video Lectures: Self-paced modules that allow you to study at your own convenience, revisiting complex concepts as needed.
- Hands-on Projects: Practical assignments where you'll work on real-world data engineering challenges, including building and optimizing data pipelines, and integrating data for AI models.
- Lab Sessions: Guided exercises and experiments that help you apply data engineering concepts using industry tools and technologies like databases, cloud platforms, and big data tools.
- Capstone Project: A final project where you will demonstrate your ability to design, implement, and optimize a data pipeline in an AI context, showcasing your learning.
- Collaborative Work: Group projects and peer collaboration to simulate real-world team environments and enhance problem-solving skills.
- Mentorship and Support: Personalized guidance from mentors to help with specific queries, project feedback, and career advice.
This approach combines flexibility, hands-on practice, and expert guidance to help you master the skills necessary for a career in AI data engineering.
Accreditation and Collaboration at TheSSML
The Standard School of Machine Learning (SSML) is committed to maintaining the highest academic and industry standards, supported by endorsements from globally recognized organizations such as the Machine Learning Accreditation Council (MACUL) and the All India Council for Technical Skill Development (AICTSD). These esteemed accreditations ensure that SSML’s initiatives align with international benchmarks, guaranteeing academic excellence and relevance in the rapidly evolving AI landscape.
In addition to these accreditations, SSML is proud to announce strategic collaborations with several distinguished academic and research institutions, as well as leading organizations across various industries. These partnerships enhance the institution's offerings, providing students with unparalleled access to cutting-edge AI research, development, and industry applications.
Key Collaborations Include:
- Ambaincip School of Business: Renowned for its focus on business innovation and entrepreneurship, Ambaincip contributes to developing AI-powered solutions to address real-world business challenges, helping students apply AI in practical business contexts.
- Narsamma School of Finance and Blockchain: This collaboration focuses on advancing AI applications within the financial sector, with a particular emphasis on blockchain, cryptocurrency, and decentralized finance (DeFi), empowering students to lead financial innovations through AI.
- Monappa School of Quantum Computing: Partnering in the realm of quantum algorithms and quantum machine learning, this collaboration offers students the opportunity to explore the intersection of quantum computing and AI, addressing complex issues that were previously unsolvable.
- Kamber School of Researchers: A research-driven institution at the forefront of pioneering AI research and development, Kamber School offers students the chance to engage in collaborative research projects with leading AI experts.
- BlackwellAi - LaB Innovation: A cutting-edge innovation lab dedicated to AI and machine learning technologies, BlackwellAi fosters the creation of AI solutions across various industries, advancing SSML’s commitment to solving global challenges with AI-driven innovations.
Impact of Collaborations:
This extensive network bridges the gap between academia, research, and industry, fostering a multidisciplinary approach to AI and machine learning development. With expertise in sectors such as finance, blockchain, quantum computing, and business innovation, SSML ensures its students receive a well-rounded education that integrates both theoretical knowledge and practical applications.
The collaborations also guarantee that SSML’s curriculum remains aligned with global standards and frameworks, including Artificial General Intelligence (AGI) and MACUL’s Machine Learning and Computational Learning guidelines, ensuring that students are equipped with the highest academic rigor while staying relevant to the dynamic global AI landscape.
Graduate Outcomes:
Graduates of SSML are equipped with both technical expertise and industry experience to drive innovative AI solutions. The institution’s emphasis on real-world applications and ethical considerations prepares students to make significant contributions to the rapidly evolving AI sector. With globally recognized credentials and world-class learning experiences, SSML graduates are prepared to lead AI innovations in various industries and create transformative impacts.
Location
Hybrid Mode
Duration
24 Months
Intakes
January, April, June & September 2025
Tuition Fees
Rs 45,000 / -
The UG Certification in AI Data Engineering is a 24 Months, comprehensive program designed to equip undergraduate students with the essential skills needed to build and manage data pipelines for artificial intelligence (AI) and machine learning (ML) applications. The program covers foundational topics such as data collection, preprocessing, integration, storage, and management, along with practical techniques for optimizing data flows to support AI-driven models.
Students will gain hands-on experience using tools and technologies like databases, cloud platforms, and big data frameworks, learning how to structure, store, and process data for real-world AI applications. The curriculum also emphasizes the role of data engineering in the development of machine learning models, focusing on data scalability, optimization, and deployment.
The program includes interactive lectures, lab sessions, real-world projects, and a capstone project, allowing students to apply their learning in practical scenarios. By the end of the program, students will be well-prepared for careers as AI Data Engineers, Machine Learning Engineers, and Data Scientists, equipped with the technical expertise required to manage large datasets and support AI development.
Programme Structure and Electives
The UG Certification in Data Engineering is a one-year program designed to provide undergraduate students with a comprehensive understanding of data engineering, combining foundational knowledge and practical skills to prepare them for successful careers in the field. The program begins by introducing key concepts in data engineering, such as data ecosystems, structures, and storage. As students progress, they will gain proficiency in both relational and non-relational databases, data warehousing, and advanced database management techniques. The program also covers essential skills for building and optimizing ETL (Extract, Transform, Load) pipelines, integrating data from multiple sources, and ensuring data quality. Students will gain hands-on experience with big data tools and cloud platforms, learning how to process large-scale data using technologies like Apache Hadoop, Apache Spark, and cloud services such as AWS and Google Cloud. In the later stages of the program, students will focus on real-time data pipelines, automation, and ensuring the security of data flows. Advanced topics in stream processing, distributed computing, and cloud-based data engineering will also be covered, providing students with a robust understanding of modern data engineering practices. By the end of the program, students will be well-prepared to take on roles as Data Engineers or related positions in the rapidly growing field of data management and analysis.
Core Periods Modules
The UG Certification in Data Engineering is a one-year program designed to provide undergraduate students with a comprehensive understanding of data engineering, combining foundational knowledge and practical skills to prepare them for successful careers in the field. The program begins by introducing key concepts in data engineering, such as data ecosystems, structures, and storage. As students progress, they will gain proficiency in both relational and non-relational databases, data warehousing, and advanced database management techniques. The program also covers essential skills for building and optimizing ETL (Extract, Transform, Load) pipelines, integrating data from multiple sources, and ensuring data quality. Students will gain hands-on experience with big data tools and cloud platforms, learning how to process large-scale data using technologies like Apache Hadoop, Apache Spark, and cloud services such as AWS and Google Cloud. In the later stages of the program, students will focus on real-time data pipelines, automation, and ensuring the security of data flows. Advanced topics in stream processing, distributed computing, and cloud-based data engineering will also be covered, providing students with a robust understanding of modern data engineering practices. By the end of the program, students will be well-prepared to take on roles as Data Engineers or related positions in the rapidly growing field of data management and analysis.
- Period 0
Introduction to Data Engineering
The "Introduction to Data Engineering" module provides foundational knowledge on data ecosystems, structures, and storage. You will learn about relational and non-relational databases, data warehousing, and basic ETL processes.
- Period 1
Source Systems, Data Ingestion, and Pipelines
The "Source Systems, Data Ingestion, and Pipelines" module focuses on understanding the various data sources and systems involved in data engineering. You will learn about structured and unstructured data, as well as the tools used for data ingestion.
- Period 2
Data Storage and Queries
The "Data Storage and Queries" module covers the essential concepts of data storage solutions and querying techniques in data engineering. You will explore various storage systems such as relational databases, NoSQL databases, and cloud-based storage solutions.
- Period 3
Data Modeling, Transformation, and Serving
The "Data Modeling, Transformation, and Serving" module focuses on the critical stages of data processing, from designing robust data models to transforming and serving data efficiently.
- Period 4
Data Modeling & Transformations for Machine Learning
The "Data Modeling & Transformations for Machine Learning" module delves into techniques for preparing and transforming data to build effective machine learning models. You will explore various data preprocessing methods, such as feature scaling, encoding categorical variables, handling missing values, and creating new features.
- Period 5
Industry Work Experience (6 Months), 2 Electives
The continuation of the work experience allows participants to deepen their expertise and apply their learning in more complex business scenarios. With additional electives, participants refine their understanding.
Electives
Electives To further tailor your learning, TheSSML offers the following electives as part of the Executive Strategic AI for Business Leaders Programme. These electives will help you specialize in areas that align with your professional interests and career aspirations.
- Profile Building++
- Decision Sciences
- Entrepreneurship & Family Enterprise
- Responsible AI and Ethical Considerations
- AI-Driven Customer Experience
- Emerging AI Technologies and Trends
- AI in Product Development
- Building AI Products
Your Future Career at TheSSML
Professionals will be equipped with the strategic and technical expertise required to lead AI initiatives across industries. As AI continues to play an increasingly pivotal role in business transformation, participants will be well-positioned for career opportunities in top technology companies, consulting firms, and multinational corporations that are integrating AI into their core operations.
Furthermore, TheSSML provides comprehensive career support, including personalized coaching, exclusive networking opportunities, and access to premium job openings within its global network. Professionals will also be eligible for opportunities with the Ambaincip School of Business, where they can apply their AI expertise to lead and innovate in high-growth, business-driven environments.
Secure Your Job at Ambaincip School of Business After Completing UG Certification in AI Data Engineering at TheSSML
Upon successful completion of the Data Engineering Professional Programme at TheSSML, you will gain exclusive access to rewarding career opportunities in collaboration with the Ambaincip School of Business. This partnership provides professionals with a unique platform to apply advanced data engineering strategies and leadership skills within a dynamic, data-driven business environment.
Ambaincip School of Business is committed to empowering graduates by placing them in influential roles where they can design and manage scalable data infrastructures, lead data-driven transformations, and optimize decision-making processes within organizations. With the comprehensive expertise gained through the program, you will be well-prepared to take on senior positions, oversee complex data projects, and make a meaningful impact on the success and growth of innovative businesses.
Secure Your Job at Ambaincip School of Business
TheSSML: Your Gateway to Innovation
At TheSSML, we cultivate a culture of curiosity, creativity, and collaboration, empowering individuals to solve complex real-world problems and contribute meaningfully to the advancement of technology. Whether you are a student, professional, or researcher, TheSSML is your gateway to mastering the skills and insights needed to lead in the rapidly evolving world of artificial intelligence and machine learning.
Fees & Admissions
Entry Requirements
Company Experience
- A minimum of 1 years of experience at a company is required, particularly in roles where you have gained exposure to AI or technology-driven projects.
- Experience in driving strategic business initiatives, AI implementations, or related fields is highly valuable.
Academic Qualifications
- A strong honours degree or its equivalent from a recognised institution.
- A compelling personal statement that showcases
- A pronounced interest in business.
- Theambition to explore beyond the confines of their initial degree discipline.
- Anaptitude for working within a multidisciplinary environment
Tuition Fees
National Applicants: Rs 45,000 / -
International Applicants: $ 527.15
We offer a range of savings and funding options. For a full breakdown of all our fees, visit our fees and funding page below.
Our Application Process at TheSSML
At TheSSML, we have simplified the application process to ensure a smooth and efficient entry into our academic community. Our clear, step-by-step application process is designed to help you prepare and submit your application with ease.
For those who might not meet the aforementioned academic criteria for the Executive Programme, consideration will be based on individual merit. Additionally, candidates who do not meet the set academic or language standards may still be eligible for entry upon successful completion of TheSSML Executive Premasters Award.
How to ApplyTop-Tier Education at TheSSML
Double Your Reach
Gain exclusive access to TheSSML's extensive alumni network, alongside global connections, enhancing your professional prospects and career opportunities.
Accredited and Recognized
TheSSML is dedicated to providing high-quality education with internationally recognized certifications, ensuring that you gain a competitive edge in the global job market.
Post-Study Career Opportunities
International students at TheSSML may benefit from career development programs and assistance in securing job placements or internships, offering valuable industry experience after graduation.
Global Partnerships
TheSSML collaborates with leading industry players, including tech giants and global corporations, to provide students with access to cutting-edge technologies, real-world learning experiences, and exciting career prospects.
Learn From the Very Best at TheSSML
At TheSSML, you will be taught by distinguished faculty members who are leaders in their fields. Our professors bring a wealth of experience from renowned global institutions and top-tier companies such as Amazon, the United Nations, IBM, Deloitte, Accenture, and Microsoft. Their extensive industry knowledge and academic expertise will provide you with the insights and practical skills needed to thrive in the dynamic world of machine learning and AI.
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TheSSML Partners with AICTSD And MACUL
At The Standard School of Machine Learning (TheSSML), our programmes are enhanced through prestigious accreditations and partnerships with leading organizations such as MACUL (Michigan Association for Computer Users in Learning) and AICTSD (All India Council for Technical Skill Development). These collaborations ensure our courses meet global industry standards and incorporate cutting-edge advancements in artificial intelligence and machine learning. The partnership with MACUL brings a rigorous framework for curriculum quality and academic excellence, while AICTSD fosters skill development and practical exposure through workshops, certifications, and real-world projects. By aligning with these esteemed bodies, TheSSML guarantees that students receive industry-recognized training, preparing them for leadership roles in a rapidly evolving AI landscape.
TheSSML Alumni Survey
At TheSSML, we are dedicated to equipping our students with the knowledge and skills needed to launch successful careers in the AI and machine learning industries. Our alumni are well-prepared to make a meaningful impact in the professional world, with many securing positions at leading global companies.
Alumni Survey (2022)
91%
of ourgraduates secured employment within six months of graduation
84%
of students received job offers before completing their programme
72%
of our alumni hold managerial or senior positions in prominent organisations
79%
of our graduates earn a competitive salary ranging from ₹8 lakhs to ₹12 lakhs per annum