Course Overview
NGDA’s Data Scientist program offers an immersive learning path to mastering machine learning (ML) and artificial intelligence (AI). Gain hands-on experience with leading tools and cutting edge technologies while developing the expertise to solve complex, real-world problems. This comprehensive program blends theoretical knowledge with practical applications, ensuring you stay ahead in the rapidly evolving fields of AI and ML
Curriculum
- 4 Sections
- 39 Lessons
- 10 Weeks
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- Bronze: $999, 1-2 months, beginner10
- 1.0Introduction to Data Science
- 1.1Python for Data Science
- 1.2Introduction to R Programming
- 1.3Foundations of Statistics (Descriptive, Probability)
- 1.4Data Cleaning and Preprocessing
- 1.5Basics of Machine Learning
- 1.6Data Visualization with Python
- 1.7Basics of Data Wrangling
- 1.8Introduction to Business Applications of Data Science
- 1.9Hands-On Project: Predictive Model
- Silver: $1,499, 2-3 months, intermediate9
- 2.0Advanced Statistics (Hypothesis Testing, ANOVA)
- 2.1Supervised Learning (Decision Trees, Random Forests)
- 2.2Unsupervised Learning (Clustering, PCA)
- 2.3Feature Engineering Techniques
- 2.4Model Evaluation and Metrics (ROC, AUC, Cross-Validation)
- 2.5Intro to Big Data for Data Science (Spark MLlib)
- 2.6Cloud Machine Learning Services (GCP, AWS ML)
- 2.7Advanced Visualization for Insights
- 2.8Hands-On Project: Real-World ML Applications
- Gold: $1,999, 3-4 months, advanced11
- 3.0Deep Learning Basics
- 3.1Advanced Machine Learning
- 3.2Natural Language Processing Basics
- 3.3Time Series Analysis and Forecasting
- 3.4Ethics in AI and Data Privacy
- 3.5MLOps and Deployment Pipelines
- 3.6Advanced Cloud ML Tools
- 3.7Domain Applications
- 3.8Research Techniques in Data Science
- 3.9Real-World Data Science Leadership
- 3.10Hands-on Project : Create a model to analyze sentiment in social media posts, reviews, or news articles.
- Platinum: $2,999, 4-6 months, expert9
- 4.0Advanced Deep Learning (Transformers, GANs)
- 4.1Reinforcement Learning
- 4.2Cutting-Edge AI Techniques
- 4.3Advanced Time Series (ARIMA, Prophet)
- 4.4AI Fairness and Explainability
- 4.5Building Scalable AI Systems
- 4.6Data Science Team Management and Mentorship
- 4.7Specialized Applications (Autonomous Systems, Edge AI)
- 4.8Capstone Project: AI-Driven Business Solutions
Instructor
