DATA SCIENCE – PROFESSIONAL PROGRAM
Industry-Aligned Training with Latest Tools & Technologies
Course Description
Program Objectives
- Build strong foundations in data science concepts & methodologies
- Master data analysis, visualization, and feature engineering
- Develop and evaluate machine learning models
- Apply deep learning and AI techniques to real-world problems
- Deploy data science solutions into production environments
- Become job-ready for data science roles
What You Will Learn
Course Curriculum
11 Sections• Introduction to Data Science & AI
• Data Science Lifecycle & CRISP-DM
• Business Problem Framing
• Data Sources & Data Collection Techniques
• Python Architecture & Environment Setup
• Data Types, Control Flow & Functions
• Object-Oriented Programming (OOP)
• Working with Files, APIs & JSON
• NumPy for Numerical Computing
• Pandas for Data Manipulation & Analysis
• Data Cleaning & Missing Value Treatment
• Exploratory Data Analysis (EDA)
• Feature Engineering Techniques
• Descriptive & Inferential Statistics
• Probability Distributions
• Hypothesis Testing
• Linear Algebra & Calculus Essentials
• Optimization Concepts
• Data Visualization Principles
• Matplotlib, Seaborn & Plotly
• Interactive Dashboards (Power BI / Tableau – Overview)
• Storytelling with Data
• Supervised & Unsupervised Learning
• Regression & Classification Algorithms
• Decision Trees, Random Forest & XGBoost
• Clustering & Dimensionality Reduction (PCA)
• Model Evaluation & Performance Metrics
• Ensemble Learning Techniques
• Time Series Analysis & Forecasting
• Recommendation Systems
• Natural Language Processing (NLP) Fundamentals
• Computer Vision Overview
• Neural Network Fundamentals
• Artificial Neural Networks (ANN)
• Convolutional Neural Networks (CNN)
• Recurrent Neural Networks (RNN / LSTM)
• Deep Learning with TensorFlow & Keras
• Introduction to Generative AI
• Prompt Engineering for Data Scientists
• Large Language Models (LLMs) Overview
• AI Ethics & Responsible AI
• AI-Powered Analytics Tools
• Model Serialization & Versioning
• Building APIs with Flask / FastAPI
• Cloud Deployment (AWS / Azure / GCP Overview)
• CI/CD for ML Pipelines
• Monitoring & Model Performance Management
• End-to-End Data Science Projects
• Predictive & Prescriptive Analytics Use Cases
• NLP / ML / AI-Based Applications
• Industry-Oriented Capstone Project
Testimonials
"The SAP FICO training was clear and practical. Trainers explained real business cases that helped me gain confidence for interviews."
"The classes were interactive and easy to follow. Placement guidance helped me prepare a strong resume and crack interviews."
"Flexible batch timings allowed me to study while working. The practical sessions improved my understanding of accounting concepts."
"The trainers provided step-by-step explanations with real examples. Certification and career support gave me confidence to apply for jobs."
"Course structure was well organized and industry focused. Mock interviews and guidance sessions prepared me for real company roles."
"Learning experience was smooth and professional. Support team responded quickly and helped me throughout the training program."
"WebProtech gave me real industry skills with hands-on training. The projects helped me gain confidence."
"The teaching style is simple and clear. I was able to switch my career into IT easily."
"Best place to learn full stack development. Trainers focus on practical learning and doubt solving."
"I loved the structured course and real-time projects. It helped me understand concepts deeply."
"WebProtech helped me improve my coding skills. The DSA training was very useful for interviews."
"Support from mentors is great. They guide you at every step and help with placement preparation."
"Very good learning environment. The course content is updated and industry-focused."
"I joined as a beginner and now I can build full stack applications. Highly recommended institute."
"The best part is hands-on practice. You don’t just learn theory, you actually build projects."
Recent Placements
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Neha Gupta
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Priya Sharma
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Rahul Verma
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Frequently Asked Questions
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