Learn from a seasoned professional with 11+ years of experience in Data Science, Machine Learning, Artificial Intelligence,
and real-world analytics system development.
Expertise in data preprocessing, exploratory data analysis (EDA), feature engineering, statistical modeling, and building scalable data-driven solutions using Python, SQL, and industry tools.
Specialized in developing supervised and unsupervised machine learning models, time series forecasting, classification, clustering, and model optimization for real business applications.
Strong foundation in neural networks, NLP basics, computer vision concepts, and deploying AI models using modern frameworks such as TensorFlow, Scikit-Learn, and cloud platforms.
Leads end-to-end analytics projects including dashboards, automation pipelines, recommendation systems, fraud detection models, and enterprise-grade AI solutions.
Whether you’re a student, fresher, or working professional, our Data Science (AI & ML) training in Hyderabad equips you with hands-on experience in Python, Machine Learning, data analytics, and real-world projects, helping you become industry-ready and confident for high-paying roles.
Our structured syllabus guides you from core data science fundamentals to building real-world analytics and machine learning solutions. Each module includes hands-on data projects, data cleaning and feature engineering exercises, model building and evaluation, visualization workflows, capstone projects, and assessments to ensure strong practical mastery and job-ready skills.
Overview of the Data Science Lifecycle
Role of a Full-Stack Data Scientist
Tools and Technologies in Full-Stack Data Science
Linear Algebra, Calculus, and Probability Basics
Statistical Distributions and Applications
Python
R Language
Data Cleaning and Transformation Techniques
Handling Missing Data, Outliers, and Data Imbalance
Feature Scaling, Encoding, and Selection
Dimensionality Reduction Techniques: PCA, t-SNE, LDA
Types of Machine Learning: Supervised, Unsupervised, Reinforcement
Algorithms: Linear Regression, Logistic Regression, Decision Trees, Random Forest, SVM, and kNN
Model Evaluation Metrics: Accuracy, Precision, Recall, F1-Score, and ROC-AUC
eural Networks: Architecture and Training
Deep Learning Frameworks: TensorFlow, PyTorch, and Keras
onvolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs)
SQL and Relational Databases
Bigdata and Hadoop
Creating Visualizations with Matplotlib, Seaborn, Plotly, and Dash
Interactive Dashboards with Power BI
Tableau Basics: Connecting, Building Dashboards, and Storytelling
Fundamentals of Business Analytics
KPI Definition and Business Intelligence
Case Studies: Sales, Marketing, and Operational Analytics
Basics of Cloud Computing and Its Importance in Data Science
Deploying Machine Learning Models on Azure and AWS
Working with Cloud Databases and Storage Solutions
Building APIs using Flask and FastAPI
Deploying Models with Docker and Kubernetes
MLOps: Monitoring and Maintaining Deployed Models
Every learner who successfully completes the training program at AimNxt receives an official Course Completion Certificate. Our certificate validates your practical skills, hands-on project experience, and industry-ready knowledge, making your resume stand out during interviews.
Complete our Data Science Course and become industry-ready for high-paying careers in Artificial Intelligence, Machine Learning, Data Engineering, Business Intelligence, and Cloud AI. Master Python, R, SQL, Hadoop, Spark, TensorFlow, PyTorch, Azure AI, Power BI, Generative AI, Prompt Engineering, Docker, Kubernetes, and MLOps through real-world enterprise projects.
Find answers to common questions about our Data Science training program, certification, and career opportunities.
