Advanced Diploma Certification Programme in Machine Learning & Artificial Intelligence
This programme is offered by TheSSML in collaboration with the Institute for AI and ML Education for Schools (IAMLES).
About the Programme
The Advanced Diploma in Machine Learning & Artificial Intelligence is a comprehensive 1-year program designed to equip learners with essential skills and hands-on experience in AI and ML technologies. This industry-relevant course covers the complete pipeline—from data handling and model building to real-world deployment—empowering students and professionals to design intelligent systems, automate processes, and innovate with emerging technologies.
Through expert-led sessions, practical projects, and case studies, learners will explore machine learning algorithms, deep learning models, natural language processing, computer vision, and responsible AI practices.
Key Skills Developed
Who is the programme for?
The Advanced Diploma Certification Programme in Machine Learning & Artificial Intelligence is designed for graduates, final-year students, and working professionals from fields like computer science, engineering, mathematics, statistics, or related domains who are eager to build a career in AI and ML. It is also ideal for data analysts, software developers, faculty members, and researchers looking to integrate AI into their work or research. Tech entrepreneurs and innovators aiming to develop AI-powered solutions will benefit from the program's practical and industry-oriented approach. Anyone with a foundational understanding of programming and mathematics, and a passion for emerging technologies, is welcome to join.
How will you study?
The Advanced Diploma in Machine Learning & Artificial Intelligence follows a hands-on, project-based learning approach designed to blend theory with real-world application. You will study through a mix of live online sessions or in-person classes, guided tutorials, interactive workshops, and peer discussions. Each module includes practical assignments, mini-projects, and case studies to reinforce learning. Industry experts and mentors will guide you through capstone projects that simulate real-world AI challenges. Additionally, you'll have access to recorded lectures, curated reading materials, and coding exercises, allowing for flexible and self-paced study alongside structured guidance.
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
Distance Mode
Duration
1 Year
Intakes
40
Tuition Fees
Rs 25000/-
The Advanced Diploma Certification Programme in Machine Learning & Artificial Intelligence is a 1-year comprehensive training program designed to build core competencies in the field of AI and ML. The curriculum combines theoretical foundations with practical skills, enabling learners to develop, train, and deploy intelligent systems using real-world datasets and modern tools. From basic data preprocessing to advanced deep learning models, the program covers a wide range of topics including supervised and unsupervised learning, neural networks, NLP, computer vision, and model deployment. With hands-on projects, industry-aligned content, and expert mentorship, this program prepares participants for high-demand roles in AI-driven industries.
Programme Structure and Electives
The Advanced Diploma in Machine Learning & Artificial Intelligence is structured into two distinct phases over a 1-year period. The first 6 months focus on intensive learning, where students build a strong foundation in machine learning, deep learning, data handling, NLP, and computer vision through hands-on training, live sessions, assignments, and mini-projects. This is followed by a 6-month internship phase, where learners apply their knowledge in real-world industry environments. During the internship, students work on live projects, collaborate with professionals, and gain practical exposure to AI applications, tools, and deployment practices—preparing them for successful careers in AI and related fields.
Core Periods Modules
The Advanced Diploma in Machine Learning & Artificial Intelligence is structured into two distinct phases over a 1-year period. The first 6 months focus on intensive learning, where students build a strong foundation in machine learning, deep learning, data handling, NLP, and computer vision through hands-on training, live sessions, assignments, and mini-projects. This is followed by a 6-month internship phase, where learners apply their knowledge in real-world industry environments. During the internship, students work on live projects, collaborate with professionals, and gain practical exposure to AI applications, tools, and deployment practices—preparing them for successful careers in AI and related fields.
- Period 0
Foundations of Artificial Intelligence & Machine Learning
– Introduction to AI & ML: Concepts, History, and Applications – Types of Machine Learning: Supervised, Unsupervised, Reinforcement – Mathematics for ML: Linear Algebra Essentials – Statistics & Probability for AI – Python Programming for Data Science – Data Preprocessing & Feature Engineering – Exploratory Data Analysis (EDA) with Pandas & Matplotlib – Introduction to Scikit-learn and Basic ML Models
- Period 1
Core Machine Learning Techniques
– Regression Techniques: Linear & Logistic Regression - Classification Algorithms: Decision Trees, KNN, SVM – Clustering Algorithms: K-Means, Hierarchical Clustering – Dimensionality Reduction: PCA & t-SNE – Model Evaluation Metrics (Accuracy, Precision, Recall, F1) – Cross-Validation & Hyperparameter Tuning – Ensemble Methods: Random Forest, Gradient Boosting, XGBoost – Real-World ML Project: Model Building & Validation
- Period 2
Deep Learning & Neural Networks
– Introduction to Neural Networks & Deep Learning – Building ANN Models with TensorFlow/Keras – Convolutional Neural Networks (CNN) for Image Recognition – Recurrent Neural Networks (RNN) and LSTM for Sequence Data – Transfer Learning with Pretrained Models – Activation Functions, Loss Functions & Optimizers – Training Techniques: Regularization, Dropout, Batch Normalization – Deep Learning Project: Image or Text-Based Application
- Period 3
Natural Language Processing & Computer Vision
– Text Preprocessing Techniques (Tokenization, Lemmatization, Stopwords) – Sentiment Analysis & Text Classification – Introduction to Word Embeddings: Word2Vec, GloVe – Transformers & BERT Models in NLP – Basics of Computer Vision & Image Processing with OpenCV – Object Detection Techniques (YOLO, SSD, Haar Cascades) – OCR & Image-to-Text with Tesseract – Capstone Mini Project: Chatbot or Vision Application
- Period 4
AI Applications, Ethics & Deployment
– AI Use Cases in Healthcare, Finance, Retail, Education – Ethical AI: Bias, Fairness, Transparency, and Accountability – Explainable AI (XAI) Techniques – Model Deployment with Flask/Streamlit – Cloud Deployment: AWS/GCP/Azure Basics – Version Control with Git & GitHub – Building APIs for AI Models – Final Capstone Project & Internship Preparation
- 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 of AI’s role in strategy and leadership, preparing them for high-level decision-making roles.
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
Completing the Advanced Diploma Certification Programme in Machine Learning & Artificial Intelligence at TheSSML opens doors to a wide range of high-demand career opportunities in the rapidly growing AI industry. With hands-on experience, real-world internship exposure, and expert mentorship, graduates will be well-prepared to take on roles such as Machine Learning Engineer, AI Developer, Data Scientist, NLP Engineer, Computer Vision Specialist, and AI Product Analyst. The program’s strong focus on industry readiness also supports entrepreneurial pathways, empowering learners to launch their own AI-driven ventures or work with cutting-edge startups. At TheSSML, your journey doesn’t end at graduation—it begins with a network of innovation, opportunity, and lifelong learning.
Secure Your Job at Ambaincip School of Business After Completing Advanced Diploma Certification Programme in Machine Learning & Artificial Intelligence at TheSSML
Securing a job at Ambaincip School of Business comes with a complete agreement that guarantees support in obtaining employment or an internship. This agreement ensures that students who successfully complete the program will receive assistance in securing job placements or internships with reputable companies. The school collaborates with industry partners, providing students with access to valuable opportunities that align with their career goals. By signing this agreement, students commit to the program's requirements while benefiting from a structured pathway to launch their careers, equipped with the practical experience and professional connections needed for job success.
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
To be eligible for admission, candidates must meet the following criteria:
- Educational Qualification:
Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or related fields. Final-year students may also apply. - Technical Skills:
Basic understanding of programming (preferably Python) and mathematics (linear algebra, probability). - Professional Background (for working professionals):
Experience in software development, data analysis, or related areas is preferred but not mandatory. - Passion for AI/ML:
A strong interest in AI, problem-solving mindset, and willingness to learn and apply new technologies.
Tuition Fees
National Applicants: Rs 25000/-
International Applicants: $ 292.86
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.
Enquire Now
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