Diploma in Artificial Intelligence & Data Science

Description

Course Name: Diploma in Artificial Intelligence & Data Science

Course Id: DAIDS/Q0001.

Eligibility: 10+2 Grade (higher secondary) or Equivalent.

Objective: The Diploma in Artificial Intelligence (AI) & Data Science course is designed to equip students with the knowledge and practical skills required to understand and work in the rapidly growing fields of artificial intelligence and data science. This course combines the theoretical aspects of AI and data science with hands-on experience, providing students with the tools to analyze and interpret complex data, design AI models, and implement machine learning algorithms.

Duration: Six Months.

 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- 120 minutes.
• No. of Questions- 60. (Multiple Choice Questions).
• 10 Questions from each module, each carry 10 marks.
• Maximum Marks- 600, Passing Marks- 40%.
• There is no negative marking in this module.

 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.

Syllabus

Introduction to Artificial Intelligence & Data Science: Definition and scope of AI and Data Science, Applications of AI in various industries, Key components of AI (ML, DL, NLP, CV), Difference between AI, ML, and Data Science, Role of Big Data in AI, Ethical considerations in AI, Fundamentals of data-driven decision-making, AI trends and future prospects, AI and automation in business, Introduction to AI frameworks and tools.

Mathematics & Statistics for AI & Data Science: Linear algebra for AI (vectors, matrices, tensors), Probability and statistics for data science, Calculus and its role in AI, Optimization techniques for machine learning, Descriptive and inferential statistics, Hypothesis testing and confidence intervals, Correlation and regression analysis, Bayesian statistics and decision theory, Numerical methods for data analysis, Case studies on mathematical applications in AI.

Programming for AI & Data Science (Python & R): Introduction to Python for AI, Basics of R programming, Data structures and algorithms in AI, Libraries for AI (NumPy, Pandas, Scikit-learn), Data preprocessing techniques, Object-oriented programming for AI, API integration in AI applications, Handling missing data and outliers, Data visualization with Matplotlib and Seaborn, Case studies on AI programming.

Data Handling and Processing: Types of data (structured, unstructured, semi-structured), Data collection and cleaning techniques, Data transformation and feature engineering, Handling large datasets (Big Data), Data integration and warehousing, SQL and NoSQL databases for AI, Data pipelines and automation, Web scraping and data extraction, Cloud-based data storage solutions, Case studies on data handling.

Machine Learning Fundamentals: Supervised vs. unsupervised learning, Classification and regression models, Decision trees and random forests, Support vector machines (SVM), K-nearest neighbors (KNN), Clustering techniques (K-Means, Hierarchical), Model evaluation and performance metrics, Feature selection and dimensionality reduction, Overfitting and underfitting, Case studies on machine learning applications.

Deep Learning & Neural Networks: Introduction to deep learning, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN) for image processing, Recurrent Neural Networks (RNN) for sequential data, Long Short-Term Memory (LSTM) networks, Autoencoders and Generative Adversarial Networks (GANs), Hyperparameter tuning and optimization, Transfer learning in deep learning, GPU acceleration for deep learning, Case studies on deep learning.

Job Opportunities after completion of Diploma in Artificial Intelligence & Data Science course: