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Data Science Track

Data Science:
Level-02

4.8 (1,230 reviews)

Advance from fundamentals to production-grade AI at Level-02. Master machine learning, ensemble models, big data & cloud platforms, and end-to-end model deployment — and build real AI solutions for healthcare, finance, IoT and beyond.

Created by Avanteia
12,580 Total Enrolled
15 September 2024 Last Updated
Enroll Now
Data Science Level-02 Course
3 Months Duration
Certificate On Completion
Level-02 Level
9 Modules Syllabus
3 Months Duration
English Language
Certificate Included

Overview

Advance from fundamentals to production-grade AI. Master machine learning, ensemble models, big data & cloud platforms, and end-to-end model deployment — with hands-on labs in every module and a real-world capstone project.

Machine Learning Ensembles Clustering Big Data & Cloud Deployment Capstone

Learning Outcome

Master advanced ML, ensembles and cloud-based big data. Optimise models for performance and ship complete solutions to the cloud.

Syllabus

Click any module to expand and view topics and hands-on labs included.

  • What is Data Science?
  • Real-world applications & career paths
  • Python fundamentals (variables, data types, loops, functions)
  • Libraries overview: NumPy, Pandas, Matplotlib
Hands-on Lab
Setup Google Colab/Jupyter Notebook Write Python programs (calculator, loops, list handling) Use Pandas to load & explore CSV data
  • Data collection (CSV, Excel, APIs, web scraping basics)
  • Cleaning missing values, duplicates, outliers
  • Encoding categorical data (One-hot, Label encoding)
  • Normalization & Standardization
  • Graphs: bar, line, scatter, histogram, boxplot, heatmaps
  • Correlation analysis
  • Feature importance overview
Hands-on Lab
Load a dataset from Kaggle Perform data cleaning using Pandas Handle missing values & outliers Use Matplotlib & Seaborn for visualization Create a heatmap of correlations Visualize trends in real-world dataset (COVID, Sales, etc.)
  • Descriptive statistics (mean, median, variance, std dev)
  • Probability distributions (Normal, Binomial)
  • Hypothesis testing (t-test, chi-square test)
Hands-on Lab
Simulate coin toss & dice using Python Perform hypothesis testing on dataset in Colab
  • SQL basics (SELECT, WHERE, JOIN, GROUP BY, HAVING)
  • Query optimization
  • Connecting SQL with Python
Hands-on Lab
Use SQLite / MySQL free version Write queries on sample dataset Integrate SQL with Pandas
  • ML pipeline (train-test split, model evaluation)
  • Regression: Linear
  • Classification: Logistic Regression, k-NN, Decision Trees
Hands-on Lab
Predict house prices (Regression) – Kaggle dataset Build a classification model (Iris dataset)
  • Random Forest, Gradient Boosting
  • Feature engineering & selection
  • Cross-validation techniques
  • k-Means Clustering
Hands-on Lab
Build a Random Forest model for Titanic survival prediction Use Scikit-learn feature selection methods
  • Hierarchical clustering
  • PCA (Dimensionality Reduction)
Hands-on Lab
Customer segmentation (K-Means) Reduce dimensions of dataset using PCA
  • Introduction to Big Data (Hadoop, Spark)
  • Cloud tools (Google BigQuery, AWS free tier, Azure ML Studio)
  • Handling large datasets efficiently
Hands-on Lab
Run queries on Google BigQuery free tier Process data using PySpark on Colab
  • End-to-End Data Science Project
  • Model deployment using Flask + Streamlit + GitHub
  • Best practices in reporting & documentation
Hands-on Lab
Choose a dataset (finance, healthcare, retail, social media) Perform EDA → ML → Visualization → Deployment Deploy on Streamlit Cloud / Heroku (free)

What You Will Learn

Advanced ML Models

Design, train and evaluate regression, classification and clustering models across real datasets.

Optimise for Performance

Apply feature engineering, ensembles and tuning to squeeze accuracy and efficiency from models.

Big Data & Cloud Integration

Handle large-scale datasets using Hadoop, Spark and cloud platforms for scalable data science solutions.

End-to-End Deployment

Deploy complete data science projects using Flask, Streamlit and cloud hosting for real-world impact.

What Our Students Say

"

The Level-02 course took my skills to a professional level. The ensemble modelling and PySpark labs are exactly what I needed to land my first data scientist job. Avanteia's hands-on approach is unmatched.

Vikram Patil Data Scientist, Mumbai
"

I completed Level-01 first and immediately enrolled in Level-02. The big data and cloud modules were eye-opening. The 3-month duration is perfect for working professionals.

Sneha Kadam ML Engineer, Pune
"

The capstone deployment module is incredibly relevant. I shipped my first Streamlit app to the cloud using the skills from this course. Highly recommended for anyone serious about data science.

Rahul Menon Data Analyst, Bangalore

Ready to Level Up Your
Data Science Career?

Join 12,580+ learners who have advanced their skills. Enroll today and get certified in just three months.

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