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Python - Artificial Intelligence and ML Training in Dehradun
Python - Artificial Intelligence and ML Training in Dehradun
The Python – AI & ML Training at A2IT InternEdge helps students and professional build real world skills in Artificial Intelligence and Machine Learning. Instead of learning theory you'll work on real projects and make your resume industry ready. This program is designed to help you build skills in python and industry tools to solve the real problems using AI.
Python Programming in Dehradun
Learn the fundamentals of python that are required to build Artificial Intelligence and Machine Learning.
Core Machine Learning Techniques in Dehradun
Learn Supervised, Unsupervised, and reinforcement techniques to understand how machine learn from data and make intelligent decisions.
Artificial Intelligence Concepts in Dehradun
Explore neural networks, NLP, and computer vision, Discover how to build smart system that can think, understand and even see like humans.
The Python – AI & ML Training at A2IT InternEdge is designed to turn your curiosity about Artificial Intelligence into real and practical skills. By working on real projects you will learn how to build intelligent systems and predictive models using AI.
You'll explore core concepts like neural networks, natural language processing(NLP), computer vision and machine learning algorithms, learn all the skills using powerful tools Numpy, Pandas, matplotlib, TensorFlow and Keras.
By the end of the course you'll have a globally recognized AI/ML certificate in hand and the confidence to begin your career as AI Engineer, ML Developer, or Data Scientist.
Faculty made it a point to provide numerous opportunities for students to be successful outside of the classroom – via internships, volunteer opportunities and job offerings.”
Maliha Alizabeth Student
Course Syllabus
Artificial Intelligence (AI) Machine Learning (ML) in Dehradun
AI, ML Syllabus — Six Months Training Plan (2025)
Duration: 4–6 months | Fee: ₹15,000 (6 months) | Experience: 24+ years
Month 1 — Programming Mathematical Foundations
Goal: Build programming and math skills necessary for ML.
Week 1: Python for Scientific Computing
Python basics, data types, NumPy for vectors & matrices.
Week 2: Algorithms & Data Structures
Functions, loops, complexity (Big-O), core data structures.
Week 3: Linear Algebra for ML
Vectors, matrices, eigenvalues/eigenvectors, PCA basics.
Week 4: Calculus & Probability
Derivatives, gradients, probability, Bayes' theorem, distributions.
Month 2 — Data Exploration & Preparation
Goal: Master EDA, visualization, feature engineering, and preprocessing pipelines.
Week 5: Exploratory Data Analysis (EDA)
Pandas, data loading, aggregation, univariate/bivariate analysis.
Week 6: Data Visualization
Matplotlib & Seaborn: histograms, boxplots, scatter, heatmaps, storytelling.
Week 7: Feature Engineering
Interaction terms, encoding categoricals, missing value strategies.
Week 8: Preprocessing & Pipelines
Scaling, outlier handling, Scikit-Learn pipelines.
Month 3 — Core Machine Learning Algorithms
Goal: Understand math, trade-offs, and implementations of core ML models.
Week 9: Regression & Classification
Linear & Logistic Regression, SVMs and kernels, hinge loss.
Week 10: Tree-Based Models & Clustering
Decision trees (Gini/Entropy), pruning; K-Means, DBSCAN.
Week 11: Advanced Unsupervised Learning
PCA deep dive, t-SNE, association rules (Apriori).
Week 12: Model Evaluation
Train/validation/test splits, cross-validation, precision/recall/F1, ROC/AUC.
Month 4 — Advanced ML & Optimization
Goal: Learn ensembles, boosting, hyperparameter tuning, and production readiness.
Week 13: Bagging & Random Forests
Bootstrapping, aggregation, Random Forest internals.
Week 14: Boosting
AdaBoost, Gradient Boosting Machines, XGBoost fundamentals.
Week 15: Model Optimization
Grid/Random Search, Bayesian optimization, bias-variance tradeoff.
Week 16: Regularization & Production
L1/L2 regularization, model serialization (pickle/joblib).
Month 5 — Deep Learning & Neural Networks
Goal: From neurons to networks — build and train neural networks.
Week 17: Introduction to Neural Networks
Perceptron, MLPs, activation functions, forward/backward propagation.
Week 18: CNNs & Computer Vision
Convolutions, pooling, architectures (LeNet, AlexNet, ResNet overview).
Week 19: RNNs, LSTMs & Sequence Models
Recurrent networks, sequence-to-sequence, attention basics.
Week 20: Training at Scale
Optimizers (Adam, RMSProp), LR schedules, regularization, dropout.
Month 6 — Deployment, MLOps & Capstone
Goal: Move models into production and complete a capstone.
Week 21: Model Deployment
Flask/FastAPI, Dockerizing models, REST APIs for inference.
Week 22: MLOps & Monitoring
Model versioning, CI/CD basics, monitoring and logging.
Week 23: Ethics & Responsible AI
Bias, fairness, privacy, interpretability, regulation.
Week 24: Capstone Presentation
Deliver capstone project with code, report, and presentation.
Additional Value Modules
- Python Basics
- Git & GitHub for Version Control
- Free Video Course with International Certification
- Majer Project & Internship Certificate
Join the AI-ML Course in Dehradun
Join the AI-ML Internship course today and gain practical skills, industrial projects, and confidence to build, deploy, and optimize intelligent systems.
Future-Ready Courses
Apply for Internship
Frequently Ask Questions
We are committed to leaving the world a better place. We pursue new technology, encourage creativity, FAQ abuot Internship and Industrial Training.
At A2IT InternEdge, AI, ML internship and course program offers flexible durations to suit your needs. While a normal internship duration is 6 months, we also offer shorter periods ranging from 45 days to 1-3 months.
at A2IT InternEdge offer both paid (stipend-based) and free internship opportunities. The type of internship you can apply for depends on the program and your qualifications. also provide course for discounted fee of Rs. 15,000 for six months.
In the internship program, you will learn the complete cycle of Artificial Intelligence and Machine Learning — from programming foundations, data exploration, and core ML algorithms to advanced deep learning, deployment, and MLOps. You will also complete hands-on projects and a capstone that prepare you for real-world applications.
Yes, upon successful completion of the internship and you will assigned a live project, project report, PPT and other required documents, you will be awarded an internship completion certificate from A2IT InternEdge.
To apply for an internship, you can either send your resume to our company email ID or contact our HR team directly. They will guide you through the next steps of the application proces.
At A2IT InternEdge, Yes, we provide both offline and online classes to accommodate your schedule and learning preferences. You can choose the mode of study that works best for you.