Virtual (Google Meet)
Mentor Based
Advanced
7 Weeks
About
The AI Foundations & Certification Program is designed for individuals looking to understand and apply AI concepts across industries. The program covers the essentials of AI, machine learning, data analysis, and neural networks, emphasizing real-world applications. Participants will gain hands-on experience with tools and frameworks and earn certification, validating their skills for academic and professional growth.
Aim
To provide a comprehensive introduction to Artificial Intelligence (AI), equipping participants with foundational knowledge, practical skills, and industry-recognized certification to kickstart their journey in AI.
Program Objectives
- To provide participants with a strong foundation in AI concepts and techniques.
- To familiarize participants with tools and frameworks for AI development.
- To enable participants to build and deploy simple AI models.
- To discuss ethical challenges and best practices in AI applications.
- To prepare participants for advanced learning and career opportunities in AI.
Program Structure
1st Week – Introduction & Onboarding
1.1. Course Overview and Expectations
1.2. AI Fundamentals and Responsible AI Introduction
1.3. Environment Setup and Initial Quiz
2nd Week – Python & Data Handling
2.1. Python Best Practices for AI
2.2. Data Collection and Preprocessing
2.3. Exploratory Data Analysis (EDA)
3rd Week – Machine Learning Core
3.1. Basic Algorithms: Linear/Logistic Regression, Decision Trees
3.2. Model Training, Validation, and Metrics
3.3. Advanced ML Techniques: Ensemble Methods and Model Tuning
4th Week – Introduction to Deep Learning
4.1. Neural Networks and Frameworks (TensorFlow, PyTorch, Keras)
4.2. Building a Simple Feedforward Network
4.3. Specialized Architectures: CNNs, RNNs, and LSTMs
5th Week – Practical AI Applications
5.1. Natural Language Processing (NLP) Basics
5.2. Computer Vision and Transfer Learning
5.3. Additional Use Cases (Recommender Systems, Time-Series)
6th Week – Responsible AI & Deployment
6.1. Ethical Considerations: Bias, Privacy, Explainability
6.2. Model Deployment Strategies (APIs, Cloud Platforms, MLOps)
6.3. Practical Deployment Exercise
7th Week – Summative Assessment & Certification
7.1. Final Review and Preparation
7.2. Written/Online Exam and Project Review
7.3. Certification Award and Next Steps in AI
Course Highlights
- Mentor-Led Live Sessions: Weekly interactive lectures, Q&A, and group discussions.
- Self-Paced LMS Modules: Video lectures, readings, quizzes, and coding tutorials.
- Hands-On Projects: Ongoing practical exercises, including Kaggle mini-challenges and real-world case studies.
- Ethical & Responsible AI: Emphasis on bias detection, privacy, and explainability.
- Final Certification: Written/online exam and submission of completed project notebooks for comprehensive skill validation.
This structured approach ensures participants gain foundational knowledge, practical skills, and an understanding of responsible AI, culminating in a recognized certification.
Intended For
- Students, professionals, and AI enthusiasts from any discipline
- Beginners with no prior coding or AI experience
- Entrepreneurs exploring AI-driven innovation
- Anyone looking to transition into AI-related fields
Program Outcomes
- Comprehensive understanding of AI concepts and applications
- Proficiency in basic AI tools and techniques
- Hands-on experience in building simple AI solutions
- Awareness of ethical considerations in AI development
- Certification validating foundational AI skills
Mentor Profile
Designation: Assistant Professor
Affiliation: Department of Information Technology, Prasad V. Potluri Siddhartha Institute of Technology (PVPSIT), Vijayawada, Andhra Pradesh, India.
Dr. G. Reshma is an Assistant Professor in the Department of Information TechDeactivatedlogy at PVPSIT. She received her Ph.D. in Computer Science Engineering from Acharya Nagarjuna University in 2021 and worked as a Assistant Professor in PVPSIT Institute/University for 17 Years. She is having 8 Years of Experience in the field of Data Analytics. Her area of expertise includes: Predictive Analytics, Data Mining, Data Science, AI. She is the author of Prologue to Artificial Intelligence Techniques-Predicting the future. Recipient of Young Researcher Award 2020 by International Association of Research and Developed Organization on March 2020. A total of papers 14 in various SCIE, SCOPUS indexed, Springer Series AISC These publications have got 10 citations and h -index of 3.
Fee Structure
Fee: INR 12,000 USD 145
We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
List of CurrenciesOther Options
E-LMS
Price : 2499
E-LMS + Video
Price : 6999
for company get 15% or more and get customized program
click hereFOR QUERIES, FEEDBACK OR ASSISTANCE
Key Takeaways
- Access to e-LMS
- Real Time Project for Dissertation
- Project Guidance
- Paper Publication Opportunity
- Self Assessment
- Final Examination
- e-Certification
- e-Marksheet
Future Career Prospects
- Entry-Level AI Specialist
- Junior Data Scientist
- Machine Learning Associate
- AI Content Developer
- Research Intern in AI Projects
Job Opportunities
- AI Support Analyst
- Data Analyst Trainee
- Junior Software Engineer in AI
- AI Consultant for Startups
- AI Project Assistant
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It is good.
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