Artificial Intelligence Training Course in Pune by Uncodemy

• History and evolution of Artificial Intelligence
• AI vs Machine Learning vs Deep Learning
• Types of AI: narrow AI and general AI
• Intelligent agents, search and problem-solving
• Real-world AI use cases across industries
• AI ethics, bias and responsible AI

• Python syntax, data types and control flow
• Functions, modules and object-oriented programming
• File handling and exception handling
• NumPy arrays and vectorised operations
• Pandas Series and DataFrames
• Jupyter Notebook workflow

• Linear algebra: vectors, matrices and matrix operations
• Calculus for optimisation: derivatives and gradients
• Probability and probability distributions
• Descriptive and inferential statistics
• Hypothesis testing and confidence intervals
• Gradient descent intuition

• Handling missing values and outliers
• Encoding categorical variables
• Feature scaling and normalisation
• Feature selection and feature extraction
• Exploratory data analysis with Matplotlib & Seaborn
• Train-test split and avoiding data leakage

• The machine learning workflow end to end
• Bias–variance trade-off
• Linear regression
• Logistic regression
• Scikit-learn pipelines
• Overfitting and regularisation (L1/L2)

• Decision Trees and Random Forest
• Support Vector Machines (SVM)
• K-Nearest Neighbours and Naive Bayes
• Gradient boosting concepts
• K-Means and hierarchical clustering
• PCA and dimensionality reduction

• Confusion matrix, precision, recall and F1-score
• ROC curve and AUC
• Regression metrics: MAE, RMSE, R²
• K-fold cross-validation
• Hyperparameter tuning: GridSearchCV and RandomizedSearchCV
• Handling imbalanced datasets

• Perceptron and multi-layer perceptron
• Activation functions and backpropagation
• Optimizers: SGD and Adam
• Building models with TensorFlow & Keras
• PyTorch tensors and training loops
• Dropout and batch normalisation
• RNN and LSTM basics

• Text preprocessing: tokenisation, stemming, lemmatisation
• Bag-of-Words and TF-IDF
• Word embeddings: Word2Vec and GloVe
• Sentiment analysis and text classification
• Transformers and the attention mechanism
• Hugging Face pipelines

• Image fundamentals with OpenCV
• Image transformations and data augmentation
• Convolutional Neural Networks (CNNs)
• Transfer learning with pre-trained models
• Object detection concepts
• Image classification project

• How LLMs work: tokens, embeddings and context windows
• Prompt engineering techniques
• Working with OpenAI APIs
• Text generation with Hugging Face Transformers
• Introduction to Retrieval-Augmented Generation (RAG)
• Responsible GenAI: hallucination and safety

• Model serialisation and saving
• Building REST APIs with FastAPI
• Version control with Git & GitHub
• Serving ML and DL models as APIs
• Model monitoring basics
• Building an end-to-end AI application

• Problem scoping and requirement analysis
• Dataset sourcing and preparation
• Model development and experimentation
• Evaluation, iteration and optimisation
• Deployment through FastAPI
• Documentation and GitHub portfolio
• Final project presentation and review

Pune offers strong and steady scope for AI engineers, because the city combines a large IT services base with a deep automotive and manufacturing technology ecosystem. Both sectors are adding machine learning, computer vision and generative AI to their products and internal operations.

Most technology hiring is concentrated around the Hinjewadi, Kharadi and Magarpatta IT hubs, where services firms, global capability centres and product teams build data and AI practices. Alongside IT, Pune's long-standing strength in automotive and industrial manufacturing creates demand for AI in areas such as predictive maintenance, visual quality inspection, supply-chain forecasting and connected-vehicle analytics. Growing fintech, e-commerce and healthcare-technology teams add further roles in fraud detection, recommendations and clinical data analysis.

When hiring freshers and career switchers, interviewers usually weigh three things above all. First, a firm grasp of machine learning fundamentals — model selection, evaluation metrics and the bias–variance trade-off. Second, performance in coding rounds, typically Python-based problem solving and data manipulation. Third, the depth of your project portfolio: candidates who can explain why they chose an approach, how they measured results and how they deployed a model tend to stand out. This course is structured around exactly these areas, with live sessions, graded projects and a deployed capstone.

The broad scope of this program means you can apply for a range of entry-level AI roles rather than a single job title. Because the curriculum covers classical machine learning, deep learning, language, vision and generative AI, you can match your applications to the kind of work you enjoy most and point to a relevant project for each role.

Over two to four years, growth usually comes from depth and ownership. Engineers who start with model building often move into owning complete pipelines, from data preparation to deployment and monitoring. Many then specialise in areas such as deep learning, computer vision or generative AI, and progress towards senior AI engineer roles. With broader system design experience, some later move into solution architecture or technical leadership positions.

AI salaries in Pune depend heavily on the role you target, your practical skills and the type of employer. IT services companies, product firms and automotive-technology teams all hire AI talent, but they structure pay differently. The ranges below are the same indicative market ranges Uncodemy uses across its course pages; they show how compensation typically widens as responsibility moves from model building to system design.

Sources reviewed: AmbitionBox, Glassdoor, Indeed and Uncodemy placement records. Reviewed: September 2026. These ranges are compiled by comparing publicly reported salary data for each role with internal placement information, and they are reviewed periodically so that they stay broadly in line with the market. They describe typical bands rather than individual offers. Actual packages in Pune depend on the employer's size and sector, the interview performance of the candidate, prior experience and the specific responsibilities of the role, so treat the table as a planning guide.

AI demand in Pune spans several industries, and Uncodemy's network of 850+ hiring partners reaches across many of them. The sectors below are where Pune-based AI skills are most commonly applied today:

• IT services: Delivery teams build ML, NLP and GenAI solutions for global clients from Pune's major IT parks.
• Automotive & manufacturing tech: Computer vision for quality inspection, predictive maintenance and connected-vehicle data analysis.
• Fintech: Fraud detection, credit risk modelling and document automation using machine learning and language models.
• E-commerce: Recommendation engines, demand forecasting, search relevance and customer support automation.
• Healthcare-tech: Medical image analysis, clinical text processing and patient data analytics under strict privacy rules.

Because every sector relies on the same core foundation of data, models and deployment, a broad AI program lets you apply across industries instead of committing to one early in your career.

Becoming an AI engineer is a sequence of skills, each building on the previous one. The seven steps below follow the order of this program, so you always know what comes next and why it matters.

1. Python fundamentals: Learn syntax, functions, data structures and libraries such as NumPy and Pandas for everyday data work.
2. Math & statistics: Build intuition for linear algebra, probability, statistics and gradients, which explain how models actually learn.
3. Data preprocessing: Clean, transform and explore data, engineer useful features and avoid leakage before any modelling begins.
4. Machine learning fundamentals: Train, evaluate and tune regression, classification and clustering models with Scikit-learn pipelines.
5. Deep learning: Build neural networks in TensorFlow, Keras and PyTorch, and understand how training and optimisation work.
6. NLP & computer vision: Apply deep learning to text and images using Hugging Face transformers and OpenCV-based pipelines.
7. GenAI, deployment & capstone: Integrate LLM APIs, serve models through FastAPI and complete a deployed, documented industry capstone.

Timeline: 5–6 months of consistent study, live sessions and project work is typically enough to become interview-ready for entry-level AI roles.

Before choosing an AI course, compare the facts that affect your outcome: duration, total learning time, live teaching, tool coverage, project depth and support after training. The table sets out these factors for this program so you can compare them with any alternative.

Within Uncodemy's own catalogue, this Artificial Intelligence course is the broader foundational program. LLM Engineering focuses narrowly on building and deploying applications powered by large language models, RAG Engineering specialises in retrieval-grounded systems built on enterprise knowledge, and AI Security concentrates on protecting AI systems. Those courses suit learners who already know which niche they want. If you are still building your base, this program covers classical ML, deep learning, NLP, vision and GenAI together, and a specialisation can follow later.

Uncodemy does not have a classroom in Pune, so Pune learners join this Artificial Intelligence program fully live online. This is not a reduced version of the course. You attend the same batches, learn from the same trainers and follow the same 13-module curriculum as learners in Uncodemy's classroom programs. Sessions run in real time, so you can ask questions, share your screen for debugging help and discuss projects with the trainer while the class is in progress.

Studying online also removes daily travel across the city, which matters for working professionals commuting to Hinjewadi, Kharadi or Magarpatta. You can pick a weekday or weekend batch around your job and revise with session recordings.

If you would rather learn in a physical classroom and are able to travel, in-person training remains available at Uncodemy's Delhi and Noida centres. The fee and curriculum are the same in both modes.

The Artificial Intelligence course runs for 5–6 months. During this time you attend 110+ live online sessions across 13 modules, finishing with a 25-hour industry capstone. Weekday and weekend batches are available, so you can choose the pace that fits your work or study schedule.

Prior machine learning experience is not expected, and Python is taught from Module 2 onward. Knowing programming fundamentals and being comfortable with basic maths and statistics will help you progress faster; Module 3 builds up the mathematics and statistics you need.

The course covers 15 tools: Python, NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn, TensorFlow, Keras, PyTorch, OpenCV, Hugging Face, OpenAI APIs, Jupyter Notebook, Git/GitHub and FastAPI. Each is used in hands-on assignments and projects rather than only demonstrated.

Yes. Module 8 covers Deep Learning & Neural Networks, Module 9 covers Natural Language Processing (NLP), and Module 10 covers Computer Vision & Image AI. Each module includes practical work using frameworks such as TensorFlow, PyTorch, Hugging Face and OpenCV.

The capstone is Module 13, AI Projects & Industry Capstone, a 25-hour project. You scope an industry-style problem, prepare data, build and evaluate a model, deploy it through FastAPI and document it on GitHub as a portfolio piece you can discuss in interviews.

Classes are live. The program includes 110+ instructor-led live sessions where you can ask questions in real time, and recordings are provided so you can revise topics or catch up on a session you could not attend.

The fee is ₹24,500 + 18% GST, which makes a total of ₹28,910. The same fee applies in all modes and cities, whether you learn live online from Pune or in a classroom at Delhi or Noida, and there are no hidden charges.

Yes, EMI starts from ₹4,818/month for 6 months.* This spreads the total fee of ₹28,910 across monthly payments. *EMI amount, tenure and eligibility may vary depending on the applicable payment or financing option.

You can request a demo session by submitting the enquiry form or calling our counsellors. Demo availability depends on the current batch schedule, and the team will share upcoming slots so you can experience the live teaching style before enrolling.

Yes, you receive Dedicated Career & Placement Assistance. This includes resume and LinkedIn guidance, mock interviews and opportunity sharing through a hiring network of 850+ companies. Assistance does not guarantee employment; outcomes depend on your skills and interview performance.

The course prepares you to apply for entry-level AI Engineer roles, which carry an indicative range of ₹4–8 LPA. Getting hired depends on your projects, interview performance and market conditions, and Uncodemy does not guarantee any specific role or salary.

Indicative ranges run from ₹4–8 LPA for Entry-Level AI Engineers to ₹15–28 LPA for Senior AI Engineers and ₹20–35 LPA for AI Solutions Architects. These are market ranges, not guaranteed outcomes; actual offers vary by role, skills, experience, employer and market conditions.

You can apply for AI Engineer, Machine Learning Engineer, Deep Learning Engineer, Computer Vision Engineer, NLP Engineer (Junior) and Generative AI Engineer roles. The broad curriculum lets you choose the direction that best matches your projects and interests.

Graduates from any discipline, working professionals, aspiring AI engineers and career changers are all eligible. You need a laptop and a stable internet connection; programming fundamentals and basic maths comfort are helpful but are built up during the course.

No. Salary ranges are indicative market figures, placement support does not guarantee employment, and review counts reflect publicly available platform information that may change over time. They are shared for transparency to help you make an informed decision.

No. Pune learners join the course live online. Uncodemy's classroom centres are in Delhi (Laxmi Nagar/Shakarpur) and Noida (Sector 1), and anyone able to travel can choose in-person training at either location.

No. It is an independent Uncodemy certificate, verifiable at certificate.uncodemy.com. Tools from these companies are taught in the course, but the certificate is not a vendor credential and implies no partnership or endorsement.