Artificial Intelligence Training near me in Delhi, India

As a Certified AI Trainer and Business Automation Consultant, I specialize in helping professionals and organizations understand, apply, and scale Artificial Intelligence for real-world impact. My training focuses on practical AI adoption — not just coding or theory — but how AI tools, automation platforms, and data-driven insights can transform how we work, teach, and innovate. Over the years, I’ve trained healthcare professionals, media teams, educators, and business leaders to embrace AI-powered solutions that improve efficiency and decision-making. My sessions bridge the gap between technical understanding and business application, making AI accessible to both technical and non-technical learners. My teaching emphasizes how to: Use AI tools to automate repetitive or manual tasks Design smart workflows using platforms like Power BI, Google Workspace, Microsoft 365, and n8n Integrate data analysis, predictive models, and chat-based assistants into daily operations Improve team productivity and accuracy through applied AI concepts I’ve mentored hundreds of working professionals on how to transition from task executors to strategic thinkers who can focus on innovation and business growth while letting automation handle the routine work. My programs are interactive, example-driven, and tailored to suit different industries — from hospital management systems to digital media production. Each session combines real-world case studies, live tool demonstrations, and guided exercises that help participants immediately apply what they learn. My goal is to make AI understandable, practical, and result-oriented — turning curiosity into capability. As a mentor, I also guide rising professionals in identifying the right skill path based on their career stage, helping them adopt automation tools, develop data literacy, and build confidence to lead AI-driven transformations in their workplace.

Hey ! This is Gayatri Rai , experienced in technical training with illustrated history of working within the proficient training and coaching industry. Trained more than 100 students to achieve their career goal in tech along with NASSCOM program. Skilled in python, SQL , Excel, Corporate communications , lecturing and leadership.

I am professional Data Science Trainer, currently work in Training company based on noida. I mentored over 200+ student in the field of data science.

DizitalAdda is India's first Digital Marketing Institute with a Corporate Environment in Delhi's Greater Kailash. We offer daily one-hour training on live projects, utilizing our top-notch corporate infrastructure. Through our partnerships with many MNCs, we provide 100% job assistance, including interview preparation and personality development, to ensure our students are career-ready after their digital marketing courses. Since 2009, we've trained over 25,000+ professionals and students from over 2,500 organizations. DizitalAdda offers 3 different digital marketing courses for job seekers, students, CAs, lawyers, teachers, housewives, and other working professionals.

Seasoned data analytics and predictive modeling professionals in Banking, Insurance and Pharma Sectors. We are a group of folks sharing common passion for analytics and creative problem solving, holding senior positions in several international banks and consulting companies. We promote analytics through our Training program as a strong problem solving platform for youngsters who share a dream to create a career in the analytics domain. Our curriculum includes: - Working knowledge of Analytics platforms/languages and reporting tools: o SAS (Base/Advances) o SQL o R o Python o Advanced Excel - Preparation for industry certifications: SAS Base and Advanced - Data manipulations & processing - Exploratory Data Analysis - Descriptive & Inferential Statistics - Modeling techniques o Predictive Modeling (e.g. Linear & Logistic regression) o Forecasting techniques/ time series modeling (e.g. ARIMA) o Machine Learning (Random Forest, Neural Network, GBM, others) o Distance-based and Non Linear Models o Clustering - Domain Expertise: o Understanding of Banking, Insurance and Pharmaceutical Sector o Case studies focused on modeling under different business domains, e.g. Credit Risk analytics in Banking (Credit Card, other unsecured and secured portfolios)

Wifilearning is one of the growing IT Training Institute in India. Ever Since we started educate people, our goals were precise and clear. To make learning relaxed, exciting and accessible to learners who are looking forward to build or modernize their career in IT Industry. We help you to find new horizon of your career. Our Ambition is to offer accessible and insightful knowledge of available technologies. Wifilearning will change the way you think about learning technologies. Full course length, relaxing way of learning with affordable price. It will give you a best experience that will certainly help for your growth. Wifilearning is here to help you to build your career in IT Industry. Wifi learning provides training with real time scenarios and live projects. Started in 2014 by two IT Professionals having the vision to educate people with IT expertise and change the view about conventional learning. Now covering almost every technology of IT Diligence. Wifilearning mission is to produce an amazing learning platform, with the help of exclusive methodologies of IT Classroom and online communicating Training courses, along with all-time support. Wifi learning is collaborated with matchless professionals of IT industries to provide you latest project management knowledge and keep you updated with enduring domain scenarios. It's significant aim is to make students learn in more Impact full way by integrate terminology with visuals and other means of technology.

4 years of teaching Data Science both offline and online. Believe in 20% theory, 70% practical and 10% project.

I completed my b. Tech from graphic era university. I have 5 years of experience in teaching which includes colleges and coaching center. I have taught subject like mathematics, science, social studies , geography upto class 10 . I have taught mathematics to engineering students for 2.5 years. I have taught pysics for class 12.

I will teach statistics and machine learning algorithms in the simplest way ever. No complex mathematics, just pure machine learning based on real life examples. All you will learn is NO NON SENSE MACHINE LEARNING..

Hi, If you are looking for Data Science help using Python, I have some solutions for you. But before that let me introduce myself. I am a Data Scientist, a Physicist and start-up founder. I spent 17 years in the United States, having done two masters, PhD and worked in fortune 500 companies. Right now I am heading a startup Learn Code Quiz in India. We execute client projects and also teach students Python, Data Science in collaboration with our parent company American Software Consulting Group. I will be happy to assist you based on my experiences gathered over the years. These are the modules I teach Module 1: Beginning Your Data Science Journey Setting Up Your Python Environment Installing Jupyter Notebook The Importance of Learning Data Science Understanding the Field of Data Science Essential Tools for Data Science Module 2: Harnessing Python and Jupyter's Power Working with Python Data Types and Operators Getting Familiar with Jupyter Notebook Exploring Basic Data Types Understanding Comparison and Logical Operators Module 3: Exploring Lists, Tuples, and Dictionaries Lists and How to Use Indexing Advanced Indexing Techniques Modifying Data Within Lists Introduction to Tuples Getting to Know Python Dictionaries Module 4: Crafting Python Functions Writing Functions in Python Working with Function Arguments Understanding Methods Creating User-Defined Functions Exploring Nested and Lambda Functions Module 5: Working with Loops and Conditionals Using Conditional Statements (If Statements) Implementing While Loops Getting Comfortable with For Loops Looping Through Dictionary Items Module 6: Navigating Data with NumPy and Pandas Introduction to 2D NumPy Arrays Iterating Over NumPy Arrays Creating DataFrames with Pandas Slicing and Filtering DataFrames with Pandas Utilizing NumPy and Pandas for Statistical Analysis Module 7: Manipulating Data with Pandas Importing and Exporting Data Understanding Pandas Objects: Series and DataFrames Common Functionality with Pandas Objects Selecting and Modifying Data with Pandas Combining and Reshaping DataFrames Module 8: Data Visualization with Matplotlib Introduction to Data Visualization Exploring Matplotlib for Plotting Creating Line Plots Generating Bar Plots Crafting Scatter Plots Understanding Histograms Customizing Graphs Exploring Line of Best Fit Delving into Box Plots Analyzing Data with Pair Plots Visualizing Time Series Data Introduction to 3D Plotting Exporting Figures for Sharing Module 9: Exploring Statistics and Probability Quiz on Statistics, Probability, and Linear Algebra Understanding Probability and Statistics Differentiating Probability vs. Statistics in Python Sampling Techniques in Python Exploring Random Variables and Probability Distributions Analyzing Probability Mass and Density Functions Module 10: Statistical Distributions and Hypothesis Testing Overview of Statistical Distributions Exploring the Uniform Distribution Understanding Bernoulli and Binomial Distributions Unveiling the Normal Distribution Investigating Exponential, Poisson, and T Distributions Confidence Intervals and Hypothesis Testing The Data Cleaning Process and Strategies Handling Missing or Duplicate Data Concluding Data Cleaning Tasks Module 11: Introduction to Exploratory Data Analysis Getting Started with Exploratory Data Analysis (EDA) Analyzing Descriptive Statistics, Frequencies, and Averages Understanding Correlation in Data Visualizing Data in EDA Data Preprocessing for Analysis Summary of Exploratory Data Analysis Module 12: Introduction to Linear Algebra Foundations of Linear Algebra Matrices and Vectors Operations with Matrices Dot Product and Cross Product Matrix Multiplication and Division Transposing Matrices Determinants, Inverses, and More Linear Independence and Eigenvalues Singular Value Decomposition (SVD) Principal Component Analysis (PCA) Maximum Likelihood Estimation (MLE) Module 13: Supervised and Unsupervised Machine Learning Overview of Supervised Machine Learning Introduction to Unsupervised Machine Learning The Basics of Data Modeling Multivariate Data Analysis with Gaussian Distributions Understanding Probabilistic Models Linear Regression: A Foundational Technique Practical Example of Linear Regression Insight into Least Squares Expanding the Scope of Linear Regression Module 14: Understanding Regression Techniques Geometry Behind Least Squares Regression Essential Concepts of Linear Regression Probabilistic Perspective on Linear Regression An Exploration of Probability in Regression Introducing Ridge Regression Unveiling the Role of Regularization The Balance Between Bias and Variance Cross-Validation: A Model Evaluation Technique Bayesian Inference: A Probabilistic Approach Applying Bayesian Concepts to a Coin Toss Example Module 15: Exploring Bayesian Methods The Essence of Bayesian Methods Instructions for Applying Bayesian Principles Bayesian Linear Regression Applications of Posterior Distribution The Concept of Active Learning Analytical Tools for Bayesian Analysis Using Lagrange Multipliers for Optimization Sparse Regression Techniques Insights into Lp Regression Module 16: Introduction to Classification Techniques Understanding Classification Optical Character Recognition with NN Classifier Exploring the K-Nearest Neighbors Classifier Statistical Foundations of Classification Unveiling Optimal Classification Strategies Embracing the Bayes Classifier Gaussian Class Conditional Densities Multivariate Gaussian Classification Plug-In Classifiers: The Practical Approach Linear Classification and Hyperplanes Generalizing Classification to Polynomial Forms Least Squares in Classification Tasks Module 17: Delving into Logistic Regression An In-Depth Look at Logistic Regression The Likelihood in Logistic Regression Unraveling the Logistic Regression Algorithm Laplace Approximation: A Probabilistic Technique Kernel Methods and the World of Gaussian Processes Expanding Features with Kernel Techniques A Comprehensive Study of Kernels Kernelized Perceptron: A Deep Dive Regression with Kernel Functions The Magical World of Gaussian Processes Module 18: The Art of Support Vector Machines Maximum Margin Classifiers: The Foundation Support Vector Machines: A Crucial Tool Primal and Dual Problems in SVM Soft-Margin SVM: Balancing Act An Introduction to Decision Trees Basics of Decision Tree Learning Algorithm The Power of Bootstrapping Bagging and Random Forest: A Closer Look Two Exciting Projects Await Module 19: Boosting and the World of Clustering Boosting: A Technique to Boost Decision Stumps Application Spotlight: Face Detection A Detailed Analysis of Boosting Unsupervised Learning: The Exploration Begins Clustering: Grouping Similar Data Points Understanding the Convergence of K-Means Real-World Applications of K-Means Clustering Module 20: Expectation-Maximization and Beyond Maximum Likelihood: Laying the Groundwork The Expectation-Maximization (EM) Algorithm Navigating the EM Algorithm EM for Handling Missing Data Soft Clustering vs. Hard Clustering Unveiling Gaussian Mixture Models A Closer Look at the M-Step An Example Run with Gaussian Mixtures EM for Generic Mixture Models Two Intriguing Projects Await Module 21: Collaborative Filtering and Topic Modeling Collaborative Filtering: A Puzzle to Solve Matrix Factorization: The Key to Model Inference Probabilistic Matrix Factorization A Dive into Topic Modeling Latent Dirichlet Allocation: Unveiling the Technique Nonnegative Matrix Factorization: Exploring the Concept Dual Objective Functions in NMF and Topic Modeling Module 22: Principal Component Analysis (PCA) Principal Component Analysis: A Dimension Reduction Technique The Fundamentals of PCA The Probabilistic Aspect of PCA The Intricacies of Kernel PCA Personalization through Dimension Reduction Crafting Recommender Systems for Travelers Module 23: Hidden Insights with Markov Models Exploring Markov Models Sequences and Their Significance The Dynamics of Markov Chains The First Order Markov Chain Delving into State and Stationary Distributions A Glimpse into Ranking Algorithms Classification: A Continuing Journey Module 24: Unveiling Hidden Patterns with HMMs and Kalman Filter Understanding Hidden Markov Models Learning the Art of HMM Kalman Filtering: An Algorithmic Marvel The Revisiting of Markov Models Mastering Kalman Filtering Techniques Module 25: Discovering Patterns with Association Analysis The World of Association Analysis and Rules Basket Processing: A Crucial Step Dependencies in Frequency Unearthing Association Rules Selecting Models and Parameters BIC: An Essential Derivative Automated Tracking of Basketball Statistics Module 26: Deep Learning and Text Analysis The Deep Learning Abyss: A Journey Commences The Intricate World of Deep Neural Networks Activation Functions: The Heart of Deep Learning Loss Functions: Understanding Model Errors Gradients and Optimization Techniques The Mathematical Formulations of Deep Neural Networks A Glimpse into Convolutional Neural Networks Handling Pixels, Edges, and Sharpening Images Module 27: Language Secrets: Ciphers, Models, and Analysis The Enigma of Ciphers Language Models: Decoding Text Patterns Sentiment Analysis: Extracting Emotions from Text The Power of Trigrams Building an Article Spinner in Python Thanks and Regards, Dr. Souptik Mukherjee

I am teaching Industry ready courses for the last 3 years to students and working professionals. I do provide Placement assistance and help students to get a place in top tier companies. I also Provide Internships to Hardworking Students.

I have done M.Tech in electronics and communications from P.TU and B.Tech from Kurukshetra University .I have total 10+ years experience in teaching electronics and computer subjects in various engineering colleges in Punjab ,Haryana and Himachal pradesh. I am Gate qualified and Net Qualified.My key skills in academics are in electromagnetics and antennas,control systems ,analog and digital electronics ,satellite communications and power electronics . Programming languages known C,C++ and Python .Recently I added Artificial intelligence and machine learning to my domain knowledge

"Math & AI Maestro | 7 Years Experience | Post-grad in ML | Actuarial Science Enthusiast | Unleashing Your Learning Potential!"

I am a Data Scientist by profession based in Hyderabad. Completed my graduation (B.tech) from IP University, Delhi in Electronics & Communication in 2020. Possess theoretical and applied knowledge in various technologies in Data Science like Machine Learning, Natural Language Processing, Computer Vision, Deep Neural Networks, Recommendation Systems, and have language proficiency in Python.

An analytics professional with more than eight year experience in diversified areas like Insurance, Banking, Marketing Analytics, Weather Analytics and High Frequency in various organizations. Apart from this, academic research and teaching practices in reputed academic institute of India. In the present organization, my role is as a Senior Manager (Methodologist) in Decision Analytics wing. More explicitly, I am engaged in banking and insurance analytics and internal R&D on predictive/classification problems using different Machine Learning and Deep learning algorithms. As a panelist participating in several campus engagement in Tier-I level institute.

I am a Python and Data Science trainer with experience in teaching Python, SQL, Excel, VBA, Power BI, and Data Analysis. I specialise in project-based learning, covering Python basics to advanced topics like NumPy, Pandas, Matplotlib, and Seaborn. My teaching style is simple, practical, and beginner-friendly, helping students build real-world skills and prepare for careers in Data Analysis and Data Science.

With over 5 years of cross-industry expertise spanning healthcare, retail, and tech, I bridge cutting-edge Machine Learning/Data Science techniques with actionable business outcomes. As a Master of Business Analytics graduate and industry practitioner (Telstra, AIHI, ProLearn), I’ve delivered 15% - 40% efficiency gains through advanced analytics, deep learning (PyTorch, TensorFlow), and scalable cloud solutions (AWS, Azure, Snowflake). My students don’t just learn algorithms - they master how to apply them to solve real-world problems, from optimizing customer experiences to revolutionizing healthcare diagnostics.

Till date I have trained 400+ individuals in this domain. Individuals range from University Students, Working Professionals & Corporates at Senior level.

I have completed my Bachelor's in Physics, Master's in Physics (Nuclear Physics), Master in Biophysics, Post Graduate Program in Data Science and a PhD Research Scholar in BioPhysics. I have been a Lecturer at the Graduation level; Later, I was a Scientific Assistant and Scientist C at NCNNUM. Later I taught as Assistant Professor (Biophysics) at UOM. Recently I have taken freelance online tutorials for Data Science with some organisations; I do freelance jobs too in the field. My skills range from computational Biophysics to programming to Machine learning.

I am an engineer passed out from Delhi Technological University and have been working in the IT Sector the last 3.5 Years. I am giving online Classes since My College Times for the last 5 Years. And also Microsoft Certified Data Engineer.. My Key Skills are SQL, Python, Tableau and Alteryx. I have worked in Dubai for 1 Year and have worked in Prestigious Companies like Air India. My Key Skills are I make my Classes engaging, Interesting and easy to digest and have been guiding College Students for Placement in Data Science Industry through my Personal Network for the last 2 Years.

I am a Data Science and Artificial Intelligence instructor with over 3+ years of experience in teaching, mentoring, and building real-world AI systems. I provide online and home tutoring for students, college learners, and working professionals in Python, Data Science, Machine Learning, SQL, and Generative AI. I hold a Bachelor of Science (Honors) in Computer Science from the University of Delhi, where I graduated with Rank 1 and a GPA of 9.77/10. I am also certified and trained in Machine Learning, Deep Learning, NLP, and MLOps, with extensive hands-on experience using Python, TensorFlow, PyTorch, SQL, Power BI, and modern AI frameworks. My key skills include Predictive Modeling, Data Analytics, Machine Learning, Deep Learning, Natural Language Processing, Large Language Models (LLMs), and AI-driven automation. I have built and deployed multiple real-world projects such as customer churn prediction systems, legal document summarizers, generative AI tools, and reinforcement learning models. I am also an international conference speaker, having delivered sessions in the USA, Germany, and India, and I am a published researcher with papers in Springer and ACM journals with 50+ citations. I regularly mentor students for projects, hackathons, interviews, and career transitions into data science and AI. My teaching style is highly practical and industry-oriented, focusing on real datasets, live coding, case studies, and interview-ready problem solving, ensuring that learners gain both strong fundamentals and real-world confidence.

Data Scientist with 5 years of experience in interpretating and analysing data to drive successful business solutions. Experienced at various machine learning models, predictive modelling, Text mining, Digital Image processing, etc. Excellent understanding of tools such as R, SAS, Python, SQL. Have taught analytics and R to around 15-20 professionals and helped them to advance their career in Data Science. Certified in Machine learning from Wiley and Cognizant.

I can teach anything related to digital marketing. I am regular blogger and have more that 500 visits per day on my website. I am planning to give my valuable knowledge to someone who need this badly. And teach him how he or she can earn a good amount of money.

2 Years of Industry experience with 1 year of experience as an Associate Data Scientist using ML algorithms, Computer Vision and NLP techniques. Working Experience & Extensive knowledge in Python, ML algorithms with libraries Such as Sk-learn, TensorFlow, NumPy, Pandas, Matplotlib, Seaborn. Used Computer Vision skills to successfully deliver Automation projects. Worked on tools like - PyCharm, Visual studio. Jupyter Notebook, Power-BI, Hadoop. Recognized and got appreciated by clients to deliver efficient solutions. Achieved Star Performer title for delivering critical projects successfully. Meticulous Associate Data Scientist accomplished in compiling, transforming, and analyzing complex information through software. Expert in machine learning and large dataset management. Demonstrated success in identifying relationships and building solutions to business problems.

I am an IT Developer – AI/ML at Sai Vending Services and hold a B.Sc. in Information Technology. I am currently building my expertise in Python, machine learning, NLP, and Generative AI through hands-on projects and structured learning. I have worked on projects such as customer segmentation and customer churn prediction, and I am currently developing an RAG-based document assistant that answers questions from SOPs and operational documents using embeddings and vector search. My goal is to apply AI to solve real-world business problems. My strengths include structured problem-solving, analytical thinking, and the ability to learn quickly.