Best Data Science with Python, Machine Learning and Gen AI Software Courses Training Institute in Hyderabad
About US
Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract insights from data. Companies are investing lot of money on managing and analysing the data. So, Learn from the best data science with Python, Machine Learning and Gen AI Software Courses Training Institute in Hyderabad. Also, become a certified data scientist under the guidance of esteemed trainer with real-time IT experience.
Top Rated Institute In India For Data Science And Blockchain. Special Thanks To All Our Trainees And Trainers !!!
PROUD TO BE ASSOCIATED WITH
ADITI Data Science with Gen AI Training Program
ADITI offers 150 DAYS (5 MONTHS COURSE) + 2 Months (Projects) Data Science training with Python from basic to advanced level. Followed by, Machine Learning, Gen AI and AI Agents with real-time projects.
Corporate Training Pricing
Market Price (Average):
INR 1 Lakh
Our Price (Limited Period Offer):
INR 48K
LET US KNOW YOUR REQUIREMENT
We believe you are not in cinemas. Our Classroom Training from Corporate Trainers with only 10 students per batch makes you feel smart. So, Join the Best Data Science Course in Hyderabad to enhance your IT career.
INTRODUCTION TO DATA SCIENCE & AI
Introduction to Data Science, Artificial Intelligence and Generative AI, Data Analytics and Business Intelligence, Data
Science Lifecycle and AI Workflow Overview, Roles and Responsibilities of Data Analyst, Data Scientist and AI
Engineer, Introduction to Machine Learning, Deep Learning and Large Language Models (LLMs), AI-Powered
Automation and Agentic Workflows, Tools and Technologies used in Data Science and AI Applications.
PYTHON FOR AI DEVELOPMENT
Python Programming Fundamentals, Data Types, Operators and Control Flow Statements, Functions and Modules,
Object Oriented Programming (OOP), Functional Programming using Lambda, Map, Filter and Decorators, Iterators,
Generators and List Comprehensions, File Handling and Exception Handling, Working with JSON and CSV Files,
Regular Expressions and Text Processing, Logging and Debugging Techniques, Type Hinting and Data Validation
using Pydantic, Working with APIs and HTTP Requests, Writing Modular Python Code for Data Science and AI
Applications.
BUSINESS STATISTICS
Introduction to Business Statistics and Data Interpretation, Measures of Central Tendency and Dispersion, Probability
and Probability Distributions, Sampling Techniques and Random Variables, Correlation and Covariance Analysis,
Hypothesis Testing and Statistical Inference, Chi-Square Test, T-Test and ANOVA, Business Forecasting and Trend
Analysis, A/B Testing and Data Driven Decision Making, Statistical Analysis using Real World Business Datasets.
SQL FOR DATA ANALYTICS
Introduction to SQL and Relational Databases, Database Design and Data Modelling Basics, Retrieving, Filtering and
Sorting Data, Aggregate Functions and Group By Operations, Joins, Subqueries and Common Table Expressions
(CTEs), Window Functions and Analytical SQL, Data Cleaning and Transformation using SQL, Query Optimisation
Techniques, SQL Integration with Python, Working with MySQL Databases for Data Analytics and Reporting
Applications.
POWER BI FOR DATA ANALYTICS
Introduction to Power BI and Data Visualisation, Data Modelling and Relationships, Power Query and Data
Transformation, DAX Functions and Calculated Measures, Dashboard Design and KPI Reporting, Interactive Reports
and Data Storytelling, Advanced Filters, Slicers and Drill Through Reports, Real Time Reporting and Business
Analytics Applications.
Introduction to Tableau and Data Visualisation, Connecting and Blending Data Sources, Data Analysis and
Dashboard Development, Calculated Fields and Parameters, Charts, Maps and Interactive Visualisations, Filters and
Data Storytelling Techniques, Dashboard Actions and Business Reporting Applications.
NumPy for Numerical Computing and Array Operations, Pandas for Data Processing and Data Analysis, Data
Cleaning and Transformation Techniques, Data Aggregation and Filtering, Working with CSV, Excel, JSON and SQL
Databases, Data Collection using APIs and External Data Sources, Working with Structured and Unstructured Data,
Working with Time Series Analysis, Data Analysis using SciPy and Statsmodels, Business Reporting and Insight
Generation using Python.
Introduction to Exploratory Data Analysis (EDA), Handling Missing Values and Outliers, Correlation and
Distribution Analysis, Feature Engineering and Data Preparation Techniques, Statistical Analysis and Data
Interpretation, Data Visualisation using Matplotlib and Seaborn, Statistical and Business Data Visualisation
Techniques, Automated Exploratory Data Analysis using Sweetviz and YData-profiling.
Introduction to Machine Learning, Supervised and Unsupervised Learning, Data Preprocessing and Feature
Engineering, Regression and Classification Models, Clustering and Dimensionality Reduction Techniques, Decision
Trees, Random Forest, XGBoost, K Means Clustering and PCA, Model Training and Evaluation, Cross Validation
and Hyperparameter Tuning, Scikit Learn Pipelines, Predictive Analytics and Business Use Cases, Model
Deployment Basics, Case Study on Customer Churn Prediction, Sales Forecasting and Recommendation Systems.
Introduction to Deep Learning and Neural Networks, ANN, CNN, RNN and LSTM Models, Transfer Learning and
Pretrained Models, TensorFlow and PyTorch Basics, Computer Vision and NLP Applications, Model Training and
Optimisation, AI Applications using Deep Learning, Case Study on Image Classification and Text Generation
Systems.
Introduction to Time Series Forecasting, Trend, Seasonality and Stationarity, Time Series Decomposition, ARIMA and
Prophet Models, Machine Learning Approaches for Forecasting, LSTM-Based Forecasting Overview, Forecasting
Applications in Business and Finance, Case Study on Sales and Demand Forecasting.
Introduction to Natural Language Processing (NLP), Text Preprocessing and Tokenisation, Text Vectorisation and
Embeddings, Sentiment Analysis and Text Classification, Named Entity Recognition (NER), Speech to Text and Text
to Speech Systems, Transformer Models and LLM-Based NLP Applications, Case Study on Chatbots, AI Assistants
and Sentiment Analysis Systems.
Introduction to MLOps and AI Engineering, AI Application Lifecycle and Deployment Workflow, Git and GitHub for
Version Control, Virtual Environments and Dependency Management, Model Serialisation and Packaging, Experiment
Tracking and Model Versioning, API Development using FastAPI, Streamlit for AI Applications, Docker Basics for
AI Deployment, Cloud Deployment Concepts and AI Application Monitoring Basics.
Introduction to Generative AI and Large Language Models (LLMs), Transformer Architecture, Tokens and
Embeddings, OpenAI, Gemini, Llama and Claude Models, Prompt Engineering Techniques, Fine Tuning vs
Prompting, Vector Databases and Semantic Search, Retrieval Augmented Generation (RAG), AI Hallucination and
Guardrails, Building AI Applications using OpenAI APIs and Hugging Face Models, Case Study on AI Powered
Chatbot and Research Assistant.
Introduction to AI Agents and Agentic AI Systems, Tool Calling, Memory and Multi Agent Workflows, LangChain,
LangGraph, LlamaIndex and CrewAI Frameworks, MCP and A2A Fundamentals, AI Workflow Automation, API
Integration with AI Agents, Case Study on AI SQL Assistant and Multi Agent Research Assistant.
Problem Definition, Data Collection and Pre-Processing, Data Analysis and Visualisation, Machine Learning and AI
Application Development, Generative AI and Automation Workflows, Model Evaluation and Deployment.
LIBRARIES
- Only 10 students per batch are allowed.
- Agency Driven Training with 100% placement assistance.
- Advanced Course Curriculum as per MNC requirements.
- Best faculty with Excellent Lab Infrastructure.
- Prepare your CV/Resume to attend Interviews and securing a Job.
- One-to-one Attention by Instructors.
- Classes with 30% theory and 70% hands-on.
- Successfully executed 50+ projects in just 3 months.
- Internship available.
All Graduates, Post Graduates, IT Professionals, Business owners, Engineers, Technologists
and anyone who are really serious about their career.
Best Data Science with Python and Machine Learning Software Courses Training Institute in Hyderabad
For PYTHON / DATA SCIENCE / ARTIFICIAL INTELLIGENCE / MACHINE LEARNING / BLOCKCHAIN / DIGITAL MARKETING CORPORATE TRAINING IN YOUR ORGANISATION, send requirements to admin@aditidigitalsolutions.com
Aditi Digital Solutions, training institute cum organisation is located only at KPHB Colony, Hyderabad.
Batch formation completely depends on first come first serve basis.
Only 10 students per batch are allowed. No further requests are entertained.
Beware of fraudsters with the name of ADITI offering discounts and advertisements.
