Course: Data Science & Machine Learning


Chapter 1: Python Crash Course:

  • Introduction to Python
  • Environment setup- Jupyter notebook
  • Crash course on basics of python

Chapter 2: Python for Data Analysis – Numpy

Chapter 3: Python for Data Analysis – Pandas

Chapter 4: Python for Data visualization – Matplotlib

Chapter 5: Python for Data visualization – Seaborn

Chapter 6: Data Capstone Project

Chapter 7: Introduction to Machine Learning

  • Supervised & Unsupervised learning
  • Statistics for machine learning.

Chapter 8: Linear Regression machine learning algorithm

Chapter 9: Logistic Regression machine learning algorithm

Chapter 10: Decision Trees & Random Forest machine learning algorithm

Chapter 11: Support Vector Machines machine learning algorithm

Chapter 12: K Nearest Neighbours machine learning algorithm

Chapter 13: K Means Clustering machine learning algorithm

Chapter 14: K fold cross validation technique

Chapter 15: Hyper tuning using GridSearchCV

Chapter 16: Natural Language Processing (NLP)

Chapter 17: Neural Nets & Deep Learning

  • Introduction to Artificial Neural Networks (ANN)
  • Installing TensorFlow
  • Perceptron Model
  • Neural Networks
  • Activation Functions
  • Cost functions & Gradient Descent
  • Backpropagation
  • Deep learning projects

Chapter 18: Convolutional Neural Network (CNN)

  • Introduction & Applications
  • Image classification using CNN

Why you should learn with us:

Highly Qualified & experienced Trainers

  • All our trainers are highly qualified Engineers with rich experience in Industry as well as academic field.

Live Instructor-led Classes (Online Training)

  • Live online classes allows direct interaction with trainer, which helps to make the class more dynamic and allows immediate answers to questions.

Hands-on Practical Assignments

  • Hands-on learning on numerous real world problems engages students in multiple modes of learning: kinesthetic, problem solving, and trial and error.

Online Assessment and Certification

  • Every course includes evaluation and assessment of your learning through online quiz and final online course certification exam.