Master Data Science from basics to advanced and build real-world solutions using data, statistics and machine learning.
Overview, Data Science Life Cycle, Applications, Career Path
Python Basics, NumPy, Pandas, Data Handling
Descriptive Stats, Probability Distributions, Hypothesis Testing
DataFrames, Indexing, GroupBy, Merging, Reshaping
Matplotlib, Seaborn, Plotly, Exploratory Data Analysis
Handling Missing Values, Outliers, Encoding, Feature Scaling
Supervised vs Unsupervised Learning, Model Evaluation
Linear Regression, Logistic Regression, Decision Trees
Clustering (K-Means, Hierarchical), PCA, Dimensionality Reduction
Cross Validation, Grid Search, Metrics, Overfitting & Underfitting
Introduction to SQL, NoSQL, Hadoop, Spark (Overview)
End-to-End Projects on Healthcare, Finance, Retail
Segment customers using clustering techniques.
Predict sales using regression algorithms.
Build a recommendation system using ML.
Detect fraudulent transactions using classification.
Analyze trends and predict stock prices.
Predict health risks using patient data.
* Salaries are indicative. Source: Glassdoor, AmbitionBox, Naukri (2024)
One of the fastest growing career paths globally.
Solve business problems and create value.
Work with data, AI, ML, statistics & more.
Excellent opportunities and promotions.
Be part of the AI and data-driven future.
High paying roles across industries.
Join thousands of students who transformed their careers with our training programs.