Data Science, AI & ML Training Program
Data Science, AI & Machine Learning Program is designed to help you become job-ready with comprehensive training from Excel and SQL to Python, Machine Learning, Deep Learning, and Big Data.
Gain hands-on experience through real-time projects, expert mentorship, and placement support — available online and offline
Course Syllabus Overview
Excel for Data Analysis
Build a solid foundation in data handling and reporting:
Excel interface, shortcuts & formatting
Formulas, functions, and conditional formatting
Data cleaning (TRIM, CLEAN, remove duplicates)
Sorting, filtering, data validation, and pivot tables
Hands-on data analysis exercises
SQL for Data Management
Learn to query, manage, and analyze data effectively:
SQL fundamentals, DBMS & RDBMS concepts
SELECT, WHERE, DISTINCT, ORDER BY, and filtering
Aggregate functions (COUNT, SUM, AVG, MIN, MAX)
Joins: Inner, Left, Right, Full, Self, Cross
Subqueries, Views, Stored Procedures, Indexes
Transactions, Exception Handling, and Case Studies
Python for Data Science
Master Python programming and its applications in analytics:
Python setup, Jupyter Notebook, Git & GitHub
Variables, operators, conditionals, loops & functions
Data structures – List, Tuple, Set, Dictionary
File handling (CSV, JSON, TXT) and custom modules
NumPy for numerical computing and linear algebra
Pandas for data manipulation, grouping, and merging
Data cleaning, feature engineering & outlier treatment
Data Visualization & Statistics
Transform raw data into insights:
Charts with Matplotlib and Seaborn (bar, line, heatmap)
Interactive visuals using Plotly
Descriptive statistics, probability distributions
Hypothesis testing, correlation, and sampling
Machine Learning
Explore predictive modeling and pattern recognition:
Supervised learning – Linear/Logistic Regression, Decision Trees, Random Forests, SVM, KNN
Unsupervised learning – Clustering, Association Rules, Recommender Systems
Model evaluation, feature selection & optimization
Artificial Intelligence & Deep Learning
Learn modern AI concepts and neural networks:
Introduction to AI, ML, and Deep Learning
Neural networks, activation & loss functions
TensorFlow & PyTorch fundamentals
CNNs for image recognition, RNNs for time series
LSTM, GRU, and Transfer Learning (VGG, ResNet)
NLP – Sentiment Analysis, NER, Text Generation
Generative Models – Autoencoders, GANs
Transformers, BERT, GPT & Explainable AI (XAI)
Model Deployment & Cloud Integration
Bring your models to life:
Model deployment with Flask, FastAPI, Streamlit
Cloud AI pipelines: AWS SageMaker, Azure AI, Google Vertex AI
Monitoring, maintenance, and scaling models
Big Data & Cloud Analytics
Master large-scale data handling:
Hadoop: Architecture & ecosystem
PySpark: Distributed computing
Hive: Querying Big Data efficiently
AWS: Cloud model deployment & integration
Agile & Scrum Methodology
Learn Agile project management and Scrum frameworks for delivering data projects in corporate environments.
Program Highlights
Instructor-Led Online & Offline Classes
Real-Time Projects & Internships
Case Studies & Cloud Deployments
Doubt-Clearing Sessions & Mentorship
Career Support & Job Assistance
Career Outcomes
Become job-ready for roles like:
Data Scientist
Machine Learning Engineer
AI Engineer
Data Analyst
Business Intelligence Developer
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