AI & Machine Learning (Python, Data Science, Generative AI) in Sangli 2026 | ABC Trainings

The programming foundation every data scientist needs.

• Core syntax, control flow, functions, modules & packages
• Data structures, file I/O, errors & exceptions, OOP
• Reference types, threading, GUI & database connectivity
• A hands-on project to lock in the fundamentals

From raw data to insight — wrangling, statistics and classical ML.

• NumPy & Pandas — arrays, DataFrames, groupby, merge, pivot, data wrangling
• Exploratory Data Analysis (EDA) with real case studies
• Data visualization — Matplotlib, Seaborn & interactive Plotly
• Statistics & hypothesis testing — t-tests, chi-square, ANOVA, p-values, A/B testing
• Data preprocessing & feature engineering
• Supervised & unsupervised learning — Naïve Bayes, Random Forest, clustering
• Forecasting — trend, seasonality, ARIMA
• Dimensionality reduction + two end-to-end projects

Classical ML through to Deep Learning with PyTorch.

• ML workflow, algorithm families, regression, classification & clustering
• Ensemble methods — XGBoost, LightGBM, AdaBoost, Gradient Boosting
• Model evaluation — precision/recall/F1, ROC-AUC, confusion matrix, cross-validation
• Hyperparameter tuning — GridSearch, RandomSearch, scikit-learn pipelines
• Deep Learning foundations — neural networks, activation, forward & backpropagation
• CNNs & RNNs — convolution, pooling, transfer learning, LSTM/GRU
• PyTorch — tensors, autograd, build & train a neural network
• Q-Learning — intro to Reinforcement Learning (agent, environment, reward)

LLMs, RAG and AI Agents — build and ship real AI systems.

• LLMs — tokens, embeddings, pre-training, RLHF
• Prompt engineering & advanced prompting
• Transformers & attention + modern NLP (BERT/GPT, Hugging Face)
• Retrieval-Augmented Generation (RAG) — vector DBs (Chroma/FAISS/Pinecone), LangChain & LlamaIndex
• AI Agents — ReAct, tool use, MCP (Model Context Protocol), CrewAI / AutoGen / LangGraph
• Fine-tuning — LoRA/QLoRA, PEFT, quantization, Ollama
• LLM & RAG evaluation — LLM-as-judge, RAGAS, prompt-injection safety
• Deployment & MLOps — FastAPI, Streamlit / Gradio, MLflow

Query, model and optimise data at the source.

• MySQL & PostgreSQL — tables, views, keys
• SELECT, JOINs, GROUP BY, window functions
• Subqueries, CTEs & query optimisation
• Aggregation functions, conditions, clauses & triggers

Turn models into dashboards leaders actually use.

• Power Query — data prep & transformation
• Data modelling, relationships & DAX
• Charts, advanced visuals & interactive reports
• Power BI Service + Power BI with SQL & Excel
• Real-world case studies & capstone dashboards

The analyst toolkit — from Pivot Tables to Solver & macros.

• Formulas, conditional formatting & data cleaning
• Pivot Tables & Charts
• Lookups — VLOOKUP, HLOOKUP, XLOOKUP
• Text, statistical & financial functions
• What-If Analysis, Solver & macros