Course Modules
Job-readiness curriculum designed for modern data challenges.
- Python Programming: Data structures, NumPy, Pandas, Matplotlib, Seaborn
- R Programming: Statistical modeling and visualization
- SQL & Databases: Relational databases, Queries, Joins, Normalization
- Data Visualization: Dashboards using Tableau and Power BI
- Probability, distributions, and hypothesis testing
- Regression analysis, correlation, and ANOVA
- Exploratory Data Analysis (EDA)
- Supervised Learning: Decision trees, random forests, SVMs
- Unsupervised Learning: Clustering, PCA, dimensionality reduction
- Model Evaluation: Accuracy, precision, recall, F1-score
- Deep Learning: Neural networks, CNNs, RNNs
- Natural Language Processing (NLP): Text mining, sentiment analysis
- Big Data Tools: Hadoop, Spark basics
- Cloud Integration: AWS/GCP for data pipelines
- Real-world projects (Finance, Healthcare, E-commerce datasets)
- Resume building and interview preparation
- Placement assistance and employer introductions
Why Join SGM for Data Science?
- Practical Approach: Focused on real-world application rather than just theory.
- Job Ready: Curriculum designed specifically for current IT industry demands.
- Advanced Tech: Hands-on training on Deep Learning and Big Data tools.