Courses > Data Science
Data Science
Data Science Course Syllabus (6 Months)
Overview
Introduction to Data Science and Python Programming
- Overview of Data Science concepts and applications
- Introduction to Python programming: syntax, data types, and control structures
- Data structures in Python: lists, tuples, dictionaries, and sets
- Libraries for Data Science: NumPy, Pandas, and Matplotlib
Data Preprocessing and Cleaning
- Techniques for handling missing data
- Data transformation: normalization and standardization
- Handling categorical data: encoding techniques
- Data imputation and outlier detection
Exploratory Data Analysis (EDA) and Visualization
- EDA techniques: summary statistics, distribution analysis, and correlation analysis
- Data visualization tools: Seaborn, Plotly, and Matplotlib
- Creating visualizations: bar charts, histograms, box plots, scatter plots, etc.
- Advanced visualization techniques: heatmaps, pair plots, and time series analysis
Introduction to Statistics for Data Science
- Descriptive statistics: measures of central tendency and dispersion
- Probability theory and probability distributions
- Inferential statistics: hypothesis testing, p-values, and confidence intervals
- Sampling techniques and error margins
Supervised Learning: Regression Techniques
- Linear regression and multiple linear regression
- Evaluation metrics: Mean Squared Error (MSE), R-squared
- Logistic regression and its applications in classification
- Model evaluation techniques: Cross-validation, ROC, and AUC
Supervised Learning: Classification Algorithms
- Decision Trees and Random Forests
- K-Nearest Neighbors (KNN)
- Support Vector Machines (SVM)
- Evaluation metrics: Accuracy, Precision, Recall, F1 Score, Confusion Matrix
Unsupervised Learning: Clustering and Dimensionality Reduction
- K-Means and Hierarchical Clustering
- DBSCAN and Gaussian Mixture Models
- Dimensionality reduction: PCA (Principal Component Analysis), t-SNE
- Applications in customer segmentation and anomaly detection
Advanced Machine Learning Algorithms
- Ensemble learning techniques: Bagging and Boosting
- Random Forest, AdaBoost, Gradient Boosting, and XGBoost
- Hyperparameter tuning and model optimization
- Model deployment and serving techniques
Deep Learning Foundations
- Introduction to neural networks and perceptrons
- Backpropagation and gradient descent optimization
- Activation functions and their role
- Regularization techniques: Dropout, L2 regularization
Convolutional Neural Networks (CNNs)
- Architecture of CNNs: convolution layers, pooling layers, and fully connected layers
- Applications in image recognition, object detection, and face recognition
- Building CNN models using TensorFlow/Keras
- Advanced techniques: Transfer learning and fine-tuning pre-trained models
Natural Language Processing (NLP)
- Text preprocessing: tokenization, stop words, and lemmatization
- Feature extraction: Bag of Words, TF-IDF, and word embeddings (Word2Vec, GloVe)
- NLP applications: Sentiment analysis, text classification, and named entity recognition (NER)
- Deep learning for NLP: RNNs, LSTMs, and Transformers
Big Data and Cloud Technologies
- Introduction to Big Data technologies: Hadoop and Spark
- Distributed computing and parallel processing
- Apache Spark for large-scale data processing
- Cloud computing platforms: AWS, Google Cloud, and Azure for data science
Capstone Project and Industry Internship
- Real-world problem-solving using all learned techniques
- End-to-end project: Data collection, cleaning, modeling, and deployment
- Industry internship for practical exposure to data science roles
- Presentation and communication of project findings
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Upcoming Training Batches
Live Virtual Class
Jan 27 - Apr 25
08:00 PM – 10:00 PM IST
Certified Instructor
Weekday Batches • 51 Sessions
INR 95,998/-
INR 49,999/-
Live Virtual Class
Jan 27 - Apr 25
08:00 PM – 10:00 PM IST
Certified Instructor
Weekday Batches • 51 Sessions
INR 95,998/-
INR 49,999/-
Live Virtual Class
Jan 27 - Apr 25
08:00 PM – 10:00 PM IST
Certified Instructor
Weekday Batches • 51 Sessions
INR 95,998/-
INR 49,999/-
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