Undergraduate Certification in AI Data Engineering & Cybersecurity
This programme is offered by TheSSML in collaboration with the Continuing Technology and Interprofessional Education (CTIPE).
About the Programme
This intensive 18-month program, available in both online and offline modalities, is meticulously designed for the next generation of data and security innovators. Embodying the rigorous academic standards of institutions like Stanford and Harvard, and the global, practical foresight of INSEAD, this certification offers a transformative journey into the critical field of AI Data Engineering & Cybersecurity.
The curriculum is structured to provide a profound understanding of foundational AI principles, robust data pipeline construction, and advanced cybersecurity strategies. The first 6 months are dedicated to immersive learning, featuring cutting-edge theoretical frameworks and hands-on projects that challenge participants to build, refine, and deploy secure and scalable data infrastructure for AI. This is followed by a 6-month intensive internship, providing invaluable practical exposure within leading organizations, fostering immediate application of learned concepts to real-world data security and engineering challenges. The final 6 months are dedicated to an industry experience module, allowing participants to integrate deeply into professional environments, contributing to live projects and solidifying their expertise in protecting and managing AI-driven data systems. Graduates emerge with a robust portfolio and the essential competencies to lead and innovate in the rapidly evolving landscape of secure data for AI.
Key Skills Developed
Who is the programme for?
This program is ideal for ambitious individuals aiming to become leaders in securing and managing data for the AI era. It caters to recent graduates from diverse STEM backgrounds (e.g., Computer Science, Engineering, Mathematics, Statistics) who possess a foundational understanding of programming and a keen interest in both artificial intelligence and robust data security.
It's also highly beneficial for existing professionals—including data engineers, cybersecurity analysts, software developers, and IT specialists—who wish to upskill, specialize in the unique challenges of AI data engineering and cybersecurity, and pivot their careers towards building resilient and protected AI systems. The program is designed for those who thrive in challenging environments and are eager to contribute to the next wave of technological advancement where data integrity and security are paramount.
How will you study?
The Undergraduate Certification in AI Data Engineering & Cybersecurity offers a flexible and comprehensive learning experience, accommodating diverse needs through its online and offline modalities.
Our Online Learning mode provides unparalleled flexibility, allowing you to access all course materials, lectures, and interactive sessions from anywhere with an internet connection. This is ideal if you have existing commitments, offering a blend of self-paced study with synchronous virtual classes and lively discussion forums. You'll engage with cutting-edge digital resources, collaborate on projects with peers globally, and receive timely feedback from instructors through our advanced virtual platforms.
For those who thrive in a more traditional and immersive environment, the Offline Learning modality offers engaging in-person classes, interactive workshops, and hands-on lab sessions at a designated campus or learning center in Vadodara, Gujarat. This mode facilitates direct, face-to-face interaction with instructors and peers, fostering immediate feedback, practical experience with dedicated equipment, and a strong sense of community. It's particularly beneficial for kinesthetic and visual learners who prefer a structured, physical learning environment.
Regardless of your chosen modality, the program's curriculum is equally rigorous, ensuring a consistent and high-quality educational experience across both formats. Our aim is to empower you with the essential knowledge and skills to excel in AI Data Engineering & Cybersecurity, all while offering the convenience and engagement that best suits your individual learning style.
Accreditation and Collaboration at TheSSML
The Standard School of Machine Learning (SSML) upholds the highest academic and industry standards, evidenced by endorsements from globally recognized bodies such as the Machine Learning Accreditation Council (MACUL) and the All India Council for Technical Skill Development (AICTSD). These accreditations ensure SSML's programs align with international benchmarks, guaranteeing academic excellence and relevance in the rapidly evolving AI landscape.
Beyond accreditation, SSML fosters strategic collaborations with distinguished academic and research institutions, alongside leading industry organizations. These partnerships enrich SSML's offerings, granting students unparalleled access to cutting-edge AI research, development, and real-world applications.
Ambaincip School of Startups: Renowned for its focus on business innovation and entrepreneurship, Ambaincip contributes to developing AI-powered solutions for real-world business challenges, equipping students to apply AI in practical business contexts.
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 spanning sectors such as finance, blockchain, quantum computing, and business innovation, SSML ensures students receive a well-rounded education integrating both theoretical knowledge and practical applications. These collaborations also guarantee SSML’s curriculum remains aligned with global standards and frameworks, including Artificial General Intelligence (AGI) and MACUL’s Machine Learning and Computational Learning guidelines. This commitment ensures students are equipped with the highest academic rigor while remaining relevant to the dynamic global AI landscape.
Graduate Outcomes:
SSML graduates are equipped with both technical expertise and extensive industry experience, poised 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 across various industries and create transformative impacts.
Location
Online And Offline
Duration
18 Months
Intakes
40
Tuition Fees
Rs 75,000 / -
The Undergraduate Certification in AI Data Engineering & Cybersecurity is a comprehensive 18-month programdesigned to transform aspiring engineers into experts at the intersection of artificial intelligence, robust data infrastructure, and advanced cybersecurity. The curriculum offers a balanced blend of rigorous academic theory and hands-on practical application, reflecting the best practices of leading global institutions.
The program's structure is unique and highly effective: the first six months focus on intensive learning, where you'll master core AI concepts, principles of scalable data engineering, and foundational cybersecurity strategies. The next six months are dedicated to a mandatory internship, providing invaluable real-world experience in a professional setting. This practical phase allows you to apply your knowledge to real industry challenges, such as building secure data pipelines for AI models or implementing threat detection systems. The final six months are spent in an industry experience module, where you will contribute to live projects, solidifying your expertise in protecting and managing AI-driven data systems, and building a crucial professional network. This structured approach ensures graduates are not only knowledgeable but also highly skilled and industry-ready, prepared to drive innovation from day one in secure AI data environments.
Programme Structure and Electives
The Undergraduate Certification in AI Data Engineering & Cybersecurity is a comprehensive 18-month journey, strategically divided into three interconnected 6-month phases. This structure ensures a holistic and practical learning experience, preparing you for immediate impact in the field. Phase 1: Immersive Learning (Months 1-6) focuses on building a robust theoretical and foundational understanding. This includes a core curriculum in mathematics for AI, machine learning fundamentals, scalable data architecture, and foundational cybersecurity principles. You'll engage in hands-on projects, implementing algorithms, building data pipelines, and establishing security protocols from scratch. You'll gain proficiency in relevant programming languages and AI frameworks, with expert-led sessions and workshops covering ethical considerations in data handling, data privacy, and emerging research in secure AI systems. Phase 2: Intensive Internship (Months 7-12) transitions you into practical application within a real-world professional setting. This involves industry placements within leading technology companies or cybersecurity firms in Vadodara, Gujarat, or other global locations, allowing you to apply learned concepts to real-world challenges. Under the guidance of industry professionals, you'll collaborate on ongoing projects, directly applying technical skills in data preprocessing, secure data storage, threat detection, and AI model protection, all while building valuable industry connections. Phase 3: Industry Experience Module (Months 13-18) solidifies your expertise and prepares you for impactful careers. This phase involves advanced, capstone-level projects simulating real industry scenarios in AI data engineering and cybersecurity. There's a strong focus on deploying secure AI data infrastructure into production, understanding MLOps security best practices, and implementing robust cyber defenses. Optional specialization tracks are available for focused study, alongside professional development workshops on career strategies, AI ethics in data security, and portfolio building, ensuring you're an industry-ready leader.
Core Periods Modules
The Undergraduate Certification in AI Data Engineering & Cybersecurity is a comprehensive 18-month journey, strategically divided into three interconnected 6-month phases. This structure ensures a holistic and practical learning experience, preparing you for immediate impact in the field. Phase 1: Immersive Learning (Months 1-6) focuses on building a robust theoretical and foundational understanding. This includes a core curriculum in mathematics for AI, machine learning fundamentals, scalable data architecture, and foundational cybersecurity principles. You'll engage in hands-on projects, implementing algorithms, building data pipelines, and establishing security protocols from scratch. You'll gain proficiency in relevant programming languages and AI frameworks, with expert-led sessions and workshops covering ethical considerations in data handling, data privacy, and emerging research in secure AI systems. Phase 2: Intensive Internship (Months 7-12) transitions you into practical application within a real-world professional setting. This involves industry placements within leading technology companies or cybersecurity firms in Vadodara, Gujarat, or other global locations, allowing you to apply learned concepts to real-world challenges. Under the guidance of industry professionals, you'll collaborate on ongoing projects, directly applying technical skills in data preprocessing, secure data storage, threat detection, and AI model protection, all while building valuable industry connections. Phase 3: Industry Experience Module (Months 13-18) solidifies your expertise and prepares you for impactful careers. This phase involves advanced, capstone-level projects simulating real industry scenarios in AI data engineering and cybersecurity. There's a strong focus on deploying secure AI data infrastructure into production, understanding MLOps security best practices, and implementing robust cyber defenses. Optional specialization tracks are available for focused study, alongside professional development workshops on career strategies, AI ethics in data security, and portfolio building, ensuring you're an industry-ready leader.
- Period 0
Fundamentals of Data Engineering for AI
Module 1.1: Data Architecture & Storage: Core concepts of data warehousing, data lakes, and modern data platforms (cloud vs. on-premise). Module 1.2: SQL & NoSQL Databases: Hands-on proficiency with relational and non-relational databases critical for large-scale data handling. Module 1.3: Python for Data Engineering: Advanced Python for data manipulation, scripting, and automation of data tasks.
- Period 1
Introduction to AI & Data Pipelines
Module 2.1: Machine Learning Fundamentals: Overview of ML algorithms, model training, and the data requirements for AI. Module 2.2: ETL/ELT Processes: Designing and implementing Extract, Transform, Load/Load, Transform pipelines for data ingestion and preparation. Module 2.3: Introduction to Cloud Data Services: Exploring foundational data services on cloud platforms (e.g., AWS S3, Google Cloud Storage, Azure Data Lake).
- Period 2
Cybersecurity & Secure Data Infrastructure
Module 3.1: Network Security & Cryptography: Understanding network protocols, firewalls, encryption, and secure communication. Module 3.2: Vulnerability Assessment & Penetration Testing Basics: Identifying and analyzing security weaknesses in systems and applications. Module 3.3: Identity & Access Management (IAM): Implementing secure authentication and authorization mechanisms for data access.
- Period 3
Secure Cloud & Big Data Architectures
Module 4.1: Cloud Security Best Practices: Securing cloud environments, compliance standards, and risk management in cloud data platforms. Module 4.2: Big Data Security: Addressing security challenges in distributed data systems like Hadoop and Spark. Module 4.3: Secure Software Development: Writing secure code, identifying common vulnerabilities (OWASP Top 10), and secure coding practices for data-intensive applications.
- Period 4
AI Security & Data Governance
Module 5.1: MLOps Security: Securing the entire machine learning lifecycle, from data ingestion to model deployment and monitoring. Module 5.2: Adversarial AI & Model Robustness: Understanding threats to AI models (e.g., adversarial attacks) and defense mechanisms. Module 5.3: Data Governance, Privacy & Compliance: Implementing data governance frameworks and ensuring adherence to regulations like GDPR and CCPA for AI data.
- Period 5
Capstone Project: Secure AI Data System
Module 6.1: Project Planning & Design: Define a real-world problem involving secure AI data, design a solution, and plan its architecture. Module 6.2: Secure System Implementation: Build and implement a secure data pipeline and integrate basic AI model protection mechanisms. Module 6.3: Security Audit & Presentation: Conduct a basic security audit of the implemented system, identify potential vulnerabilities, and present the final project, demonstrating both data engineering and cybersecurity expertise.
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
Your Future Career at TheSSML
The Standard School of Machine Learning (TheSSML) ensures a strong career trajectory for its graduates, evidenced by impressive placement rates: 90% of graduates secure roles within six months, with 84% receiving job offers even before program completion. For those completing programs like the Undergraduate Certification in Generative AI Engineering, TheSSML opens doors to diverse, in-demand roles such as Generative AI Engineer, Prompt Engineer, Machine Learning Engineer, AI/ML Research Scientist, and Data Scientist (with an AI focus). The institution's dedicated Career Advancement Centre offers comprehensive support, including resume building, interview preparation, and personalized job search assistance. Crucially, strategic partnerships with leading tech giants like Google, Microsoft, Amazon, Tesla, and IBM, alongside financial powerhouses such as J.P. Morgan and Goldman Sachs, provide exclusive access to internships and direct recruitment, while collaboration with Ambaincip School of Business further equips graduates to apply AI solutions to real-world business challenges.
Secure Your Job at Ambaincip School of Business After Completing Undergraduate Certification in AI Data Engineering & Cybersecurity at TheSSML
Securing a position at Ambaincip School of Business, particularly after completing TheSSML's Undergraduate Certification in AI Data Engineering & Cybersecurity, presents a highly promising career path due to their close collaboration. You can leverage this primary advantage through TheSSML's Career Advancement Centre for personalized coaching and job search assistance, which includes exclusive opportunities at Ambaincip School of Startups. To maximize your chances, align your application with Ambaincip's strong focus on business innovation and secure AI integration. Highlight how your skills in building robust, secure data pipelines and protecting AI systems can solve real-world business challenges, drive entrepreneurial ventures, and ensure data integrity. Emphasize practical projects and demonstrable results from your program, showcase any business acumen, and tailor your narrative to align with Ambaincip's values of innovation, problem-solving, and a multidisciplinary approach.
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 75,000 / -
International Applicants: $ 877.55
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