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AI Course

Our AI program provides a deep dive into the world of artificial intelligence, covering essential topics such as machine learning, data analytics, natural language processing, and automation. With hands-on projects and real-world applications, you’ll gain the skills needed to develop AI-driven solutions across industries. This program is perfect for both beginners and professionals looking to advance their careers in AI

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GEN AI Course

Why learn AI Course Now

Enhanced Employability: AI skills make students more attractive to a broad range of employers.

Higher Salary Potential: Proficiency in AI can lead to high-paying roles across many industries.

Cutting-Edge Skills: Students gain hands-on experience with the latest AI technologies and tools.

Future Readiness: Prepares students for future advancements in technology and new job roles.

Global Career Prospects: AI expertise opens doors to international job markets and remote work opportunities.

You will be master in

Machine Learning Engineer

Data Scientist

Data Engineer

Data Analyst

NLP Engineer

ML Ops Engineer

Deep Learning Specialist

AI Operations Engineer

Data Visualization Specialist

Computer Vision Engineer

Why learn AI Course Now

Foundations of AI and Machine Learning: Develop a solid understanding of AI concepts, algorithms, and real-world applications.

Deep Learning Fundamentals: Learn to build and train neural networks for advanced AI solutions.

Natural Language Processing (NLP): Master techniques for text analysis, sentiment detection, and conversational AI systems.

Computer Vision: Understand and implement image recognition, object detection, and video analytics.

Data Preprocessing and Feature Engineering: Learn methods to clean, transform, and prepare data for AI models.

 Predictive Modeling and Analytics: Build models to forecast trends and make data-driven decisions.

AI for Structured Data: Work with numerical and categorical datasets for applications like regression and classification.

AI Ethics and Interpretability: Understand the importance of fairness, bias mitigation, and explainable AI

Real-world AI Projects: Gain hands-on experience by working on AI applications across various domains like healthcare, finance, and retail.

Course Details

100% Online Learning: Flexible and self-paced courses, accessible anytime, anywhere.

 Hands-On Training: Gain practical experience by working on real-world use cases and industry-relevant projects.

Expert-Led Sessions: Learn directly from industry professionals and AI experts.

Certification: Earn a globally recognized certificate upon course completion.

Career Support: Access resume-building workshops, mock interviews, and job placement assistance.

Learner Career Outcomes

Employment in AI-related Roles

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Learners will secure roles such as AI Developer, Data Scientist, Machine Learning Engineer, etc.

Industry-Specific Expertise

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Learners will specialize in AI applications across multiple industries like healthcare, finance, and retail etc

Higher Earning Potential

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Learners will have access to higher-paying roles in the tech sector, with potential for rapid salary growth.

Advanced Research Opportunities

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Learners will be well-equipped for academic or corporate research roles in cutting-edge AI and machine learning technologies.

Entrepreneurship in AI

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Learners will be capable of launching AI-focused startups or working as independent consultants in AI.

About the Course

Our AI training program is designed to equip learners with the skills and knowledge needed to excel in the fast-evolving field of artificial intelligence. With a comprehensive curriculum covering machine learning, deep learning, natural language processing, and computer vision, the program emphasizes practical, hands-on learning through real-world projects. Taught by industry experts, it prepares students for high-demand roles like AI Developer, Data Scientist, and Machine Learning Engineer. Whether you’re starting your career or upskilling, our program ensures you are ready to master the future of AI and achieve your career goals.

What We Offer

Mastery over Variety: Instead of spreading ourselves thin, we prioritize depth and mastery, equipping you with the critical skills needed to stand out

Expert-Led Curriculum: Learn from professionals in the field who have firsthand knowledge in these fields and are fervently committed to AI and generative AI

Real-World Applications: Our courses are designed to equip you with practical information that may be used right away to real-world problems in industry or research.

Future-Proof Skills: AI and Generative AI are transforming the future of technology, ensuring that individuals stay ahead in the evolving digital landscape

Course Syllabus

Level

Duration

Fee

Discount

Total

Core

60 Hours

₹ 45,000

₹15,000

₹ 30,000

Advanced

90 Hours

₹ 60,000

₹15,000

₹ 45,000

Expert

120 Hours

₹ 75,000

₹15,000

₹ 60,000

AI Course certification

At the end of this course, you will receive a comprehensive AI Course Certification, designed to validate your expertise in the rapidly evolving field of Artificial Intelligence. This certification recognizes your mastery of key AI concepts, including machine learning, deep learning and natural language processing. It reflects your ability to apply these advanced techniques to solve real-world problems and develop innovative solutions. With AI becoming a critical skill across industries, holding this certification positions you as a valuable asset in the job market, giving you a competitive edge in landing roles in AI development, data science, and other cutting-edge tech fields.

Our certification is not only a testament to your technical skills but also an acknowledgment of your commitment to continuous learning and professional growth. Endorsed by industry experts and aligned with the latest trends, this certification holds significant value among employers, demonstrating that you possess practical, industry-relevant skills. Whether you’re looking to advance in your current role or pivot to a new career in AI, this certification equips you with the credentials that are highly sought after by leading tech companies and startups alike.

AI Master Course Trainer Profile

Our AI Master Program trainers are industry-renowned professionals with extensive knowledge of artificial intelligence, machine learning, and data science. With a strong foundation in research and real-world implementation, they combine technical prowess, practical experience, and a passion for
teaching to guide students through the complexities of AI. Their mission is to equip students with the expertise and skills necessary to thrive in today’s AI-driven world.

  1. Vast Experience in AI & Machine Learning
    o Over 10+ years of experience in AI, including areas such as machine learning, natural language processing, and computer vision.
  2. Focus on Hands-on Learning
    o Known for leading interactive workshops, case studies, and projects that empower students to apply AI techniques to solve real-world challenges.
  3. Expertise in End-to-End AI Solutions
    o Hands-on experience in designing, developing, and deploying AI models, including supervised and unsupervised learning techniques and reinforcement learning.
  4. Industry Impact with AI Innovations
    o Involved in AI-driven projects in top industries, delivering impactful solutions in sectors such as healthcare, finance, retail, and automotive.
  5. Advanced AI Qualifications
    o Holds a Ph.D. or Master’s degree in Computer Science, Data Science, or a related field, coupled with industry-recognized certifications in AI and machine learning.
  6. Passionate About AI Education & Mentorship
    o A dedicated trainer with a proven track record of mentoring over 500+ students and professionals across the globe, ensuring they bridge the gap between AI theory and practice.
  7. Experienced in AI Frameworks & Tools
    o Deep expertise in leveraging AI frameworks such as TensorFlow, PyTorch, Scikit- learn, and cloud-based platforms like Google Vertex AI, AWS SageMaker, and Azure AI.
  8. Researcher & Contributor to AI Innovation
    o Authored multiple research papers published in leading AI journals and conferences, pushing the boundaries of AI research and development.
  9. Collaborative AI Expert with Industry Ties
    o Actively collaborates with research institutions and AI-focused companies, ensuring continuous exposure to emerging technologies and the latest AI breakthroughs.
  10. AI Thought Leader & Speaker
    o Frequently invited to speak at international AI conferences, panels, and webinars, where they share insights on AI trends, innovations, and real-world applications.

AI Courses

  1. Introduction to AI and ML Concepts (4 hours)
    • Evolution of AI and ML
    • Key Terminologies: AI, ML, and Data Science
    • Types of Machine Learning: Supervised, Unsupervised, Reinforcement
    • Real-World Applications of AI and ML
  2. Statistics and Probability for Machine Learning (6 hours)
    • Descriptive Statistics: Mean, Median, Mode, Variance
    • Probability Distributions and Sampling
    • Hypothesis Testing and Confidence Intervals
  3. Advanced Exploratory Data Analysis (4 hours)
    • Data Cleaning and Pre processing
    • Outliers, Missing Values, and Feature Engineering
    • Univariate, Bivariate, and Multivariate Analysis
  4. Machine Learning Algorithms (7hours)
    • Linear and Logistic Regression
    • Model Evaluation Metrics and Optimization
  5. Data Science Project Life Cycle (6 hours)
    • Problem Identification and Hypothesis Framing
    • Data Collection, Cleaning, and Integration
    • Model Development and Evaluation
    • Deployment and Monitoring
  6. Neural Networks and Deep Learning (1 hours)
    • Introduction to Neural Networks and Activation Functions
  7. Industry-Wide AI Use Cases (8 hours)
    • Demand forecasting
    • Customer churn prediction
    • Product recommendations
    • Anomaly detection in financial transactions
  8. Natural Language Processing (9 hours)
    • Text Pre processing and Representation (TF-IDF, Word2Vec)
    • Named Entity Recognition and Topic Modeling
    • Sentiment Analysis and Chatbots
  9. Data Visualization and Communication (3 hours)
    • Basics of Data Visualization: Principles and Tools
    • Creating Visualizations with Python (Matplotlib, Seaborn)
  10. Data Engineering Fundamentals and MLOps (2 hours)
    • Data Pipelines and ETL Processes
  11. Capstone Project (10 hours)
    • Problem Definition and Dataset Preparation
    • Implementation of ML Models
    • Deployment and Performance Monitoring
    • Final Presentation and Report
  1. Introduction to AI and ML Concepts (4 hours)
    • Evolution of AI and ML
    • Key Terminologies: AI, ML, and Data Science
    • Types of Machine Learning: Supervised, Unsupervised, Reinforcement
    • Real-World Applications of AI and ML
  2. Statistics and Probability for Machine Learning (6 hours)
    • Descriptive Statistics: Mean, Median, Mode, Variance
    • Probability Distributions and Sampling
    • Hypothesis Testing and Confidence Intervals
  3. Advanced Exploratory Data Analysis (5 hours)
    • Data Cleaning and Pre processing
    • Outliers, Missing Values, and Feature Engineering
    • Univariate, Bivariate, and Multivariate Analysis
    • Dimensionality Reduction Techniques
  4. Machine Learning Algorithms (12 hours)
    • Linear and Logistic Regression
    • Decision Trees, Random Forests, and Gradient Boosting
    • Model Evaluation Metrics and Optimization
  5. Data Science Project Life Cycle (6 hours)
    • Problem Identification and Hypothesis Framing
    • Data Collection, Cleaning, and Integration
    • Model Development and Evaluation
    • Deployment and Monitoring
  6. Neural Networks and Deep Learning (3 hours)
    • Introduction to Neural Networks and Activation Functions
    • Training Deep Learning Models and Optimization
    • Convolutional and Recurrent Neural Networks
  7. Industry-Wide AI Use Cases (20 hours)
    • Demand forecasting
    • Customer churn prediction
    • Fraud detection
    • Object detection and recognition
    • Text summarization and keyword extraction
    • Product recommendations
    • Anomaly detection in financial transactions
  8. Natural Language Processing (9 hours)
    • Text Pre processing and Representation (TF-IDF, Word2Vec)
    • Named Entity Recognition and Topic Modeling
    • Sentiment Analysis and Chatbots
  9. Data Visualization and Communication (6 hours)
    • Basics of Data Visualization: Principles and Tools
    • Creating Visualizations with Python (Matplotlib, Seaborn)
    • Dashboards and Storytelling with Tableau/Power BI
  10. Data Engineering Fundamentals and MLOps (4 hours)
    • Data Pipelines and ETL Processes
    • Introduction to Big Data Tools (Hadoop, Spark)
  11. Capstone Project (15 hours)
    • Problem Definition and Dataset Preparation
    • Implementation of ML Models
    • Deployment and Performance Monitoring
    • Final Presentation and Report
  1. Introduction to AI and ML Concepts (4 hours)
    • Evolution of AI and ML
    • Key Terminologies: AI, ML, and Data Science
    • Types of Machine Learning: Supervised, Unsupervised, Reinforcement
    • Real-World Applications of AI and ML
  2. Statistics and Probability for Machine Learning (8 hours)
    • Descriptive Statistics: Mean, Median, Mode, Variance
    • Probability Distributions and Sampling
    • Hypothesis Testing and Confidence Intervals
    • Bayesian Inference and Decision Making
  3. Advanced Exploratory Data Analysis (5 hours)
    • Data Cleaning and Pre processing
    • Outliers, Missing Values, and Feature Engineering
    • Univariate, Bivariate, and Multivariate Analysis
    • Dimensionality Reduction Techniques
  4. Machine Learning Algorithms (17 hours)
    • Linear and Logistic Regression
    • Decision Trees, Random Forests, and Gradient Boosting
    • Support Vector Machines and k-Nearest Neighbours
    • Model Evaluation Metrics and Optimization
  5. Data Science Project Life Cycle (6 hours)
    • Problem Identification and Hypothesis Framing
    • Data Collection, Cleaning, and Integration
    • Model Development and Evaluation
    • Deployment and Monitoring
  6. Neural Networks and Deep Learning (4 hours)
    • Introduction to Neural Networks and Activation Functions
    • Training Deep Learning Models and Optimization
    • Convolutional and Recurrent Neural Networks
    • Transfer Learning and Advanced Architectures
  7. Industry-Wide AI Use Cases (22 hours)
    • Demand forecasting
    • Customer churn prediction
    • Fraud detection
    • Object detection and recognition
    • Text summarization and keyword extraction
    • Product recommendations
    • Anomaly detection in financial transactions
    • Crop health monitoring using satellite/drone imagery
  8. Natural Language Processing (12 hours)
    • Text Pre processing and Representation (TF-IDF, Word2Vec)
    • Named Entity Recognition and Topic Modeling
    • Sentiment Analysis and Chatbots
    • Large Language Models and Transformers (BERT, GPT)
  9. Data Visualization and Communication (10 hours)
    • Basics of Data Visualization: Principles and Tools
    • Creating Visualizations with Python (Matplotlib, Seaborn)
    • Dashboards and Storytelling with Tableau/Power BI
    • Communicating Insights Effectively
  10. Data Engineering Fundamentals and MLOps (12 hours)
    • Data Pipelines and ETL Processes
    • Introduction to Big Data Tools (Hadoop, Spark)
    • MLOps Concepts: CI/CD for ML Models
    • Monitoring and Maintenance of Deployed Models
  11. Capstone Project (20 hours)
    • Problem Definition and Dataset Preparation
    • Implementation of ML Models
    • Deployment and Performance Monitoring
    • Final Presentation and Report

AI Program – FAQ’s

  1. What is Generative AI, and how is it different from traditional AI?
    Generative AI focuses on creating new content, such as text, images, and music, using AI models. Unlike traditional AI, which focuses on pattern recognition and decision-making, Generative AI is designed to generate original content that mimics real-world data.
  2. What will I learn in the Generative AI training program?
    The program covers key concepts of Generative AI, including AI fundamentals, generative models, text and image generation, and practical applications. You will learn to use tools and frameworks to build models capable of creating new content and transforming various industries.
  3. Do I need a background in AI or programming to join this course?
    While a basic understanding of AI or programming is helpful, it is not mandatory. The course starts with foundational concepts and gradually progresses to more advanced topics. We ensure that beginners can keep up while also providing deeper insights for those with experience.
  4. What kind of projects will I work on during the course?
    You will work on hands-on projects such as generating text using AI, creating AI-generated art, and building applications that utilize generative models. These projects are designed to simulate real-world use cases of Generative AI across different industries.
  5. What certification will I receive after completing the Generative AI program?
    Upon successful completion, you will receive a Generative AI Program Certification, which validates your expertise in this specialized area of AI. This certification is highly regarded by employers seeking professionals skilled in emerging AI technologies.
  6. How can this Generative AI certification benefit my career?
    Generative AI is rapidly growing in fields like entertainment, design, marketing, and automation. This certification will position you as an expert in a niche field of AI, helping you stand out to employers who are looking for innovative professionals capable of implementing AI-driven solutions.
  7. What tools and technologies will I learn during the program?
    You will gain hands-on experience with key AI tools and technologies, including frameworks like TensorFlow and PyTorch, as well as tools for generating text (like GPT-based models) and images. You’ll also explore cloud-based AI services that support generative tasks.
  8. Is there any mentorship or support during the course?
    Yes, you will have access to expert instructors and a support team throughout the course. We offer live Q&A sessions, discussion boards, and one-on-one mentorship to ensure you get the help you need with your learning and projects.
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