Description
Certification Name: Certificate in AI & Machine Learning Professional
Course Id: CAIMLS/Q0001.
Eligibility: Graduation or Equivalent.
Objective: The Certified AI & Machine Learning Professional course is designed to equip participants with the knowledge and skills to develop, implement, and manage artificial intelligence and machine learning solutions. The course covers foundational concepts in AI, supervised and unsupervised learning, deep learning, neural networks, natural language processing, and computer vision.
Duration: Three Month.
How to Enroll and Get Certified in Your Chosen Course:
Step 1: Choose the course you wish to get certified in.
Step 2: Click on the “Enroll Now” button.
Step 3: Proceed with the enrollment process.
Step 4: Enter your billing details and continue to course fee payment.
Step 5: You will be redirected to the payment gateway. Pay the course and exam fee using one of the following methods:
Debit/Credit Card, Wallet, Paytm, Net Banking, UPI, or Google Pay.
Step 6: After successful payment, you will receive your study material login ID and password via email within 48 hours of fee payment.
Step 7: Once you complete the course, take the online examination.
Step 8: Upon passing the examination, you will receive:
• A soft copy (scanned) of your certificate via email within 7 days of examination.
• A hard copy (original with official seal and signature) sent to your address within 45 day of declaration of result.
Step 9: After certification, you will be offered job opportunities aligned with your area of interest.
Online Examination Detail:
Duration- 60 minutes.
No. of Questions- 30. (Multiple Choice Questions).
Maximum Marks- 100, Passing Marks- 40%.
There is no negative marking in this module.
| Marking System: | ||||||
| S.No. | No. of Questions | Marks Each Question | Total Marks | |||
| 1 | 10 | 5 | 50 | |||
| 2 | 5 | 4 | 20 | |||
| 3 | 5 | 3 | 15 | |||
| 4 | 5 | 2 | 10 | |||
| 5 | 5 | 1 | 5 | |||
| 30 | 100 | |||||
| How Students will be Graded: | ||||||
| S.No. | Marks | Grade | ||||
| 1 | 91-100 | O (Outstanding) | ||||
| 2 | 81-90 | A+ (Excellent) | ||||
| 3 | 71-80 | A (Very Good) | ||||
| 4 | 61-70 | B (Good) | ||||
| 5 | 51-60 | C (Average) | ||||
| 6 | 40-50 | P (Pass) | ||||
| 7 | 0-40 | F (Fail) | ||||
Key Benefits of Certification- Earning a professional certification not only validates your skills but also enhances your employability. Here are the major benefits you gain:
Practical, Job-Ready Skills – Our certifications are designed to equip you with real-world, hands-on skills that match current industry demands — helping you become employment-ready from day one.
Lifetime Validity – Your certification is valid for a lifetime — no renewals or expirations. It serves as a permanent proof of your skills and training.
Lifetime Certificate Verification – Employers and institutions can verify your certification anytime through a secure and reliable verification system — adding credibility to your qualifications.
Industry-Aligned Certification –All certifications are developed in consultation with industry experts to ensure that what you learn is current, relevant, and aligned with market needs.
Preferred by Employers – Candidates from ISO-certified institutes are often prioritized by recruiters due to their exposure to standardized, high-quality training.
Free Job Assistance Based on Your Career Interests – Receive personalized job assistance and career guidance in your preferred domain, helping you land the right role faster.
Assessment Modules:
Module 1: Foundations of Artificial Intelligence and Machine Learning: Introduction to AI and ML, History and Evolution of AI, Types of Machine Learning (Supervised, Unsupervised, Reinforcement), Mathematical Foundations (Linear Algebra, Calculus basics), Probability and Statistics for ML, Ethical Considerations in AI
Module 2: Data Preprocessing and Exploration: Data Collection and Cleaning, Handling Missing Values and Outliers, Feature Scaling and Normalization, Feature Engineering Techniques, Exploratory Data Analysis (EDA), Data Visualization Tools and Techniques
Module 3: Supervised Learning Algorithms: Linear Regression and Evaluation Metrics, Logistic Regression and Classification, Decision Trees and Random Forests, Support Vector Machines (SVM), k‑Nearest Neighbors (k‑NN), Model Evaluation and Cross‑Validation
Module 4: Unsupervised Learning and Clustering: Clustering Techniques (k‑Means, Hierarchical), Dimensionality Reduction (PCA, t‑SNE), Association Rule Learning (Apriori), Anomaly Detection Methods, Evaluation of Clustering Results, Applications of Unsupervised Learning
Module 5: Deep Learning and Neural Networks: Introduction to Neural Networks, Activation Functions and Backpropagation, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and LSTM, Deep Learning Frameworks (TensorFlow/PyTorch basics), Hyperparameter Tuning and Optimization
Module 6: Deployment and Real‑World Applications: Model Deployment Strategies (APIs, Cloud), Model Monitoring and Maintenance, Natural Language Processing (NLP basics), Computer Vision Use Cases, Reinforcement Learning Applications, Case Studies and Industry Projects
Job Opportunities After Certificate in AI & Machine Learning
Careers in AI, ML, NLP, computer vision, data science, automation, and AI product management across IT, fintech, healthcare, research, and enterprise sectors.
Top Roles: Machine Learning Engineer, AI Engineer, Data Scientist, AI Research Analyst, NLP Engineer, Computer Vision Engineer, AI Automation Specialist, AI Product Manager, AI Ethics & Governance Specialist, AI Consultant, Entrepreneur / AI Startup Founder
Key Skills: Machine learning, deep learning, NLP, computer vision, Python/R, AI model deployment, data analysis, predictive modeling, RPA integration, AI ethics, cloud AI services
Earnings (India):
Entry-level: ₹4 – 10 LPA
Mid-level: ₹12 – 25 LPA
Senior / Lead / Consultant: ₹25 – 60+ LPA
Entrepreneurial / Startup: ₹0 – Crores (performance-based)
Industries: IT & software services, BFSI, healthcare, manufacturing, e-commerce, government & smart city projects, EdTech, research labs
Scope: Rapid career growth from engineer/analyst to AI architect, consultant, or startup founder; opportunities in research, product development, automation, and leadership; high demand for AI specialists with global and remote work potential.
