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AI & Machine Learning Excellence

Data Science & Machine Learning

Transform data into insights and build intelligent systems. Master analytics, visualization, machine learning, and AI with industry-standard tools and frameworks.

Choose Your Specialization

Two career-focused tracks for the data-driven future

Analytics Track

Data Analytics & Visualization

Turn raw data into actionable insights. Master statistical analysis, data visualization, and business intelligence to drive data-informed decisions.

  • Python for data analysis (Pandas, NumPy)
  • Statistical analysis and hypothesis testing
  • Data visualization (Matplotlib, Seaborn, Plotly)
  • SQL and database management
  • Business intelligence tools (Tableau/Power BI)
  • Real-world analytics projects
ML/AI Track

Machine Learning & AI

Build intelligent systems that learn from data. Master ML algorithms, deep learning, and AI deployment for cutting-edge career opportunities.

  • Machine learning fundamentals & algorithms
  • Deep learning with TensorFlow/PyTorch
  • Natural Language Processing (NLP)
  • Computer Vision applications
  • Model deployment and MLOps
  • AI project portfolio development
14
Week Program
28
Live Sessions
12
Max Students/Batch
8+
Hands-on Projects

Tools & Technologies You'll Master

Industry-standard tech stack used by leading data teams

🐍
Python
🐼
Pandas
📊
NumPy
📈
Matplotlib
🗄️
SQL
🧠
Scikit-learn
🔥
TensorFlow
⚡
PyTorch
📊
Tableau
☁️
AWS
📓
Jupyter
🐙
Git

Data Analytics & Visualization

Transform data into compelling stories and insights

Who This Is For

  • Business Analysts: Level up from Excel to Python and advanced analytics
  • Recent Graduates: Break into data analyst roles with practical skills
  • Career Switchers: Transition into high-demand data careers
  • Marketing/Sales Professionals: Make data-driven decisions with confidence
  • Entrepreneurs: Analyze your business metrics like a pro

Comprehensive Curriculum

Weeks 1-4: Foundations
  • Python for data analysis
  • Pandas & NumPy mastery
  • Data cleaning & preprocessing
  • Exploratory Data Analysis
  • Statistical fundamentals
Weeks 5-8: Visualization
  • Matplotlib & Seaborn
  • Interactive plots (Plotly)
  • Dashboard creation
  • Tableau/Power BI basics
  • Storytelling with data
Weeks 9-11: SQL & Databases
  • SQL fundamentals
  • Complex queries & joins
  • Database design basics
  • Working with APIs
  • Data pipeline creation
Weeks 12-14: Projects
  • Business analytics project
  • Customer segmentation
  • Sales forecasting
  • A/B testing analysis
  • Portfolio capstone

Real-World Projects

  • E-commerce Analytics: Analyze customer behavior, conversion funnels, and revenue trends
  • Marketing Campaign Analysis: Measure campaign effectiveness and ROI
  • Financial Dashboard: Interactive dashboard for tracking KPIs and metrics
  • Customer Churn Prediction: Identify at-risk customers using statistical analysis
  • Sales Forecasting: Time series analysis for inventory planning

Career Outcomes

Graduates are prepared for roles like Data Analyst, Business Analyst, Analytics Consultant, Marketing Analyst, and BI Developer. Average starting salaries range from $60K-$85K depending on location and experience.

Tools You'll Use Daily

Python (Pandas, NumPy, Matplotlib, Seaborn, Plotly) • SQL (PostgreSQL, MySQL) • Jupyter Notebooks • Tableau or Power BI • Git & GitHub • Excel (advanced techniques)

Start Your Analytics Journey

Machine Learning & Artificial Intelligence

Build intelligent systems that learn and adapt

Prerequisites

This is an advanced track requiring:

  • Strong Python programming skills
  • Understanding of statistics and linear algebra
  • Experience with NumPy and Pandas
  • Basic knowledge of data analysis
  • Completion of Analytics track or equivalent knowledge

ML Curriculum

Weeks 1-4: ML Foundations
  • Machine learning concepts
  • Supervised learning
  • Linear & logistic regression
  • Decision trees & ensembles
  • Model evaluation metrics
Weeks 5-7: Advanced ML
  • Unsupervised learning
  • Clustering & dimensionality
  • Feature engineering
  • Hyperparameter tuning
  • Cross-validation techniques
Weeks 8-11: Deep Learning
  • Neural networks fundamentals
  • TensorFlow & PyTorch
  • CNNs for computer vision
  • RNNs & LSTMs for sequences
  • Transfer learning
Weeks 12-14: Specialization
  • NLP & text processing
  • Model deployment (Flask/FastAPI)
  • MLOps basics (Docker, CI/CD)
  • Cloud ML (AWS SageMaker)
  • Capstone AI project

Advanced Projects

  • Image Classification: Build a CNN to classify images with 95%+ accuracy
  • Sentiment Analysis: NLP model to analyze customer reviews and feedback
  • Recommendation System: Netflix-style content recommendation engine
  • Chatbot Development: AI-powered conversational agent using transformers
  • Object Detection: Real-time object detection using YOLO or similar
  • Predictive Maintenance: ML model for industrial equipment failure prediction

Industry-Aligned Curriculum

Our ML curriculum is inspired by AWS Machine Learning Specialty certification and industry best practices. You'll learn the same tools and techniques used by ML engineers at leading tech companies.

Deployment & MLOps

Learn to take models from notebook to production:

  • Model Serving: Deploy models as REST APIs using Flask/FastAPI
  • Containerization: Package ML applications with Docker
  • Cloud Deployment: Deploy on AWS, GCP, or Azure
  • Monitoring: Track model performance and data drift
  • CI/CD: Automate model training and deployment pipelines

Career Paths

Our ML graduates pursue roles including:

  • Machine Learning Engineer ($90K-$130K)
  • AI/ML Developer ($85K-$120K)
  • Data Scientist ($80K-$125K)
  • Computer Vision Engineer ($95K-$140K)
  • NLP Engineer ($90K-$135K)
  • MLOps Engineer ($95K-$130K)

Program Details

  • Duration: 14 weeks intensive (28 sessions)
  • Schedule: 2 sessions/week, 2 hours each
  • Batch Size: Max 12 students for focused mentoring
  • Format: Live coding sessions + project work
  • Support: 1-on-1 doubt clearing + community
  • Certificate: Upon successful project completion

Build AI Systems Today