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Data Science Track

Data Science

Combine statistics, programming, AI and machine learning to extract insights from data and solve real business problems — with hands-on projects using industry-standard tools and real-world datasets.

Duration5 Months
ModeClassroom / Online
LevelBeginner → Intermediate
Batch SizeSmall batches
Python SQL NumPy Pandas Scikit-learn TensorFlow Power BI
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Course Fees
Contact for Fees
Flexible EMI options available
  • ✓ Certificate on completion
  • ✓ Free demo class before enrolling
  • ✓ Placement assistance included
  • ✓ Capstone project & portfolio
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Syllabus

What you'll learn, module by module.

⬇ Download Full Syllabus (PDF)

1Python & Statistics›
Python programming for data science, statistics and probability.
  • Python programming fundamentals for data science
  • Descriptive statistics and probability distributions
  • Hypothesis testing and statistical inference
  • NumPy for numerical computing
2Data Wrangling & EDA›
Data collection, cleaning, preprocessing and exploratory data analysis.
  • Data collection from files, APIs and databases
  • Data cleaning — missing values, duplicates and outliers
  • Data preprocessing — encoding, scaling and transformation
  • Exploratory Data Analysis (EDA) with Pandas, Matplotlib and Seaborn
3Machine Learning›
Supervised and unsupervised learning, feature engineering and model evaluation.
  • Supervised learning — regression and classification algorithms
  • Unsupervised learning — clustering and dimensionality reduction
  • Feature engineering and feature selection techniques
  • Model evaluation metrics and cross-validation
4Deep Learning & NLP›
Deep learning fundamentals, natural language processing and time series analysis.
  • Deep learning fundamentals — neural networks with TensorFlow/Keras
  • Natural Language Processing — text preprocessing and sentiment analysis
  • Time series analysis and forecasting basics
  • Introduction to CNNs and RNNs
5Model Deployment›
Recommendation systems, AI applications and model deployment basics.
  • Building recommendation systems
  • Real-world AI application case studies
  • Model deployment basics — packaging a model as an API
  • Introduction to model monitoring in production
6Capstone Project›
An end-to-end data science project from raw data to a deployed model.
  • End-to-end project — from raw data to a deployed model
  • Data pipeline design, model training and evaluation
  • Deployment as a simple web app/API
  • Project documentation and presentation
Hands-on Projects

Build a portfolio, not just a certificate.

Customer Churn Prediction House Price Prediction Sales Forecasting Credit Risk Analysis Sentiment Analysis Movie Recommendation System End-to-End Data Science Capstone Project
Career Opportunities

Where this course can take you.

Data Scientist Machine Learning Engineer AI Engineer Data Analyst Data Engineer NLP Engineer Analytics Consultant
Certification

Finish with proof of what you can build.

🎓

Netwisdom Infotech Course‑Completion Certificate

Awarded on completion of the Data Science track and its capstone project — documenting the exact skills and project you delivered, ready to show employers.

FAQs

Common questions about this course.

?Do I need a coding background to join?›
No — each course starts from the fundamentals. Some tracks move a little faster if you already know basic programming, but no prior experience is required.
?Is this course available on weekends?›
Yes. Weekday, weekend and evening batches are available — pick whichever fits your schedule during enrollment or the free demo class.
?Will I get a certificate?›
Yes, every course ends with a course‑completion certificate documenting the exact skills and capstone project you delivered.
?Is placement assistance included?›
Yes. All courses include resume reviews, mock interviews and referrals to our hiring partners once you're ready — see the Training & Placement page for the full process.
?Who should enroll in this course?›
Ideal for BE/B.Tech, MCA, MSc and BCA students, working professionals, software developers and anyone aspiring to a career in Data Science and AI.
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