Data Science using ML
Data Science using ML
Description
GRAStech's Data Science and Machine Learning solutions unlock the hidden potential within your data. By combining advanced statistical techniques with cutting-edge algorithms, we extract valuable insights, predict future trends, and optimize business decisions. Our expertise empowers organizations to make data-driven transformations and achieve sustainable growth.
What You will Learn?
- Overview of Data Science
- Definition and Scope
- Excel Basic to Advanced
- Mathematics for Data Science
- Python for Data Science
Topics for this course
Total learning: 66 Topics
• Overview of Data Science
o Definition and Scope
o Applications and Industry Use Cases
• Data Science Pipeline
o Data Collection
o Cleaning, Exploration
o Modeling
o Deployment
1. Introduction to Excel
2. Excel Interface
3. Basic Functions and Formulas
4. Basic Data Entry and Formatting
5. Advanced Formulas
6. Data Management
7. Conditional Formatting
8. Data Analysis and Visualization
9. Charts and Graphs
10. Pivot Tables
11. Data Validation
12. Complex Formulas
• Linear Algebra
o Vectors, Matrices, and Operations
o Eigenvalues and Eigenvectors
• Probability and Statistics
Probability Distributions
o Statistical Inference
o Hypothesis Testing and Confidence Intervals
• Python for Data Science
o Python Basics to core and Data Structures
o Libraries: NumPy, pandas, Matplotlib, Seaborn
• SQL and Database Management
o SQL Queries and Operations
o DDL
o DML
o Relational Databases
• Data Visualization
o Creating Visualizations with Matplotlib, Seaborn, ggplot2
o Advanced Visualization Techniques (Interactive Dashboards)
• Supervised Learning
o Regression (Linear Regression, Polynomial Regression)
o Classification (Logistic Regression, Decision Trees, Random Forests)
o Model Evaluation and Hyperparameter Tuning
• Unsupervised Learning
o Clustering (K-means, Hierarchical Clustering)
o Dimensionality Reduction (PCA, t-SNE)
• Advanced Machine Learning
o Ensemble Methods (Boosting, Bagging)
o Support Vector Machines (SVM)
o Neural Networks Basics
1. Introduction to NLP
• What is NLP?
Definition and Scope
o Applications and Use Cases
• History and Evolution
• NLP Pipeline
o Text Processing and Understanding
2. Text Preprocessing
3. Text Generation and Summarization
• Text Generation
• Text Summarization
4. Sentiment Analysis and Opinion Mining
1. Use of cloud computing
1. Data Science and Business Intelligence
• Capstone Project
o End-to-End Data Science Project
o Real-World Problem Solving
Opportunities after this course completion
Data Science and Machine Learning
Price: INR 35000
This Course Includes
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Skill level : Advanced
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Duration : 4 Months
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Chapters : 8
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Topics : 66
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Language : English
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Certificate : Yes
