Pay After Placement - Data Science & Machine Learning Program

  Foundations: Mathematics & Statistics Essentials

- Introduction to Mathematics
- Coordinate Geometry
- Linear Algebra
- Eigenvalues, Eigenvectors, and Eigendecomposition
- Introduction to Calculus
- Understanding Data
- Descriptive Statistics
- Data Visualization
- Probability
- Probability Distributions
- Sampling and Sampling Techniques
- Inferential Statistics
- Application of Inferential Statistics
- Relationship Between Variables
- Application of Statistics in Business

  Foundations: Programming Refresher

- Fundamentals of Programming
- Introduction to Python Programming
- Python Data Types and Operators
- Conditional Statements and Loops in Python
- Python Functions
- Object-Oriented Programming Concepts with Python
- Threading

  Foundations: Python for Data Science

- Python Basics
- Python Data Structures
- Python Programming Fundamentals
- Working with Data in Python
- Working with NumPy Arrays

  Core: Applied Data Science with Python

- Introduction to Data Science
- Essentials of Python Programming
- NumPy
- Linear Algebra
- Statistics Fundamentals
- Probability Distributions
- Advanced Statistics
- Working with Pandas
- Data Analysis
- Data Wrangling
- Data Visualization
- End-to-End Statistics Application in Python

  - Machine Learning Fundamentals
- Supervised Learning
- Regression Models and Applications
- Classification Models and Applications
- Unsupervised Learning
- Ensemble Learning
- Recommendation Systems

  Core: Deep Learning with TensorFlow

- Introduction to Artificial Intelligence and Deep Learning
- Artificial Neural Network
- Deep Neural Network and Tools
- Optimization, Tuning, and Interpretability of Deep Neural
- Networks
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks
- Autoencoders

  Core: Deep Learning Specialization

- Introduction to Deep Learning
- Artificial Neural Networks
- Deep Neural Networks
- TensorFlow
- Model Optimization and Performance Improvement
- Convolutional Neural Networks (CNNs)
- Transfer Learning
- Object Detection
- Recurrent Neural Networks (RNNs)
- Transformer Models for Natural Language Processing (NLP)
- Getting Started with Autoencoders
- PyTorch

  Core: Essentials of Generative AI, Prompt Engineering & ChatGPT

- Generative Al and its Landscape
- Explainable Al
- Conversational Al
- Prompt Engineering
- Designing and Generating Effective Prompts
- Large Language Models
- ChatGPT and its Applications
- Fine-tuning ChatGPT
- Ethical Considerations in Generative Al Models
- Responsible Data Usage and Privacy
-The Future of Generative Al
- Al Technologies for Innovation

  Interview Blitz

- Practice multiple timed mock assessments
- Perfect the art of cracking DSA interviews through multiple DSA Blitz sessions
- Prepare to defend every single skill keyword added to your resume

  TheSkillians Externship

Unlike regular boot camps where you wrap up your learnings with a Capstone project, we go one step further. You will actually work on a real project statement given by some of the top tech companies in India. Here are some of the past companies who provided externships for our learner community.