Machine Learning, Python Course
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Machine Learning, Python Course
Course Detail
Machine Learning, Python
Get ready to dive into the world of Machine Learning (ML) by using Python! This course is for you whether you want to advance your Data Science career or get started in Machine Learning and Deep Learning.This course will begin with a gentle introduction to Machine Learning and what it is, with topics like supervised vs unsupervised learning, linear & non-linear regression, simple regression and more. You will then dive into classification techniques using different classification algorithms, namely K-Nearest Neighbors (KNN), decision trees, and Logistic Regression. You’ll also learn about the importance and different types of clustering such as k-means, hierarchical clustering, and DBSCAN. With all the many concepts you will learn, a big emphasis will be placed on hands-on learning. You will work with Python libraries like SciPy and scikit-learn and apply your knowledge through labs. In the final project you will demonstrate your skills by building, evaluating and comparing several Machine Learning models using different algorithms. By the end of this course, you will have job ready skills to add to your resume and a certificate in machine learning to prove your competency
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Enroll today and learn something new.Syllabus
Module 1
Introduction to Data Science:
- What is Data Science?
- What does Data Science involve?
- Era of Data Science
- Business Intelligence vs Data Science
- Life cycle of Data Science
- Tools of Data Science
- Introduction to Python
Module 2
Data Extraction, Wrangling, & Visualization:
- Data Analysis Pipeline
- What is Data Extraction?
- Types of Data
- Raw and Processed Data
- Data Wrangling
- Exploratory Data Analysis
- Visualization of Data
Module 3
Introduction to Machine Learning with Python:
- Python Revision (numpy, Pandas, scikit learn, matplotlib)
- What is Machine Learning?
- Machine Learning Use-Cases
- Machine Learning Process Flow
- Machine Learning Categories
- Linear regression
- Gradient descent
Module 4
Supervised Learning – I:
- What is Classification and its use cases?
- What is Decision Tree?
- Algorithm for Decision Tree Induction
- Creating a Perfect Decision Tree
- Confusion Matrix
- What is Random Forest?
Dimensionality Reduction:
- Introduction to Dimensionality
- Why Dimensionality Reduction?
- PCA
- Factor Analysis
- Scaling dimensional model
- LDA
Career Opportunities
- Machine Learning Engineer
- Data Scientist
- Natural Language Processing (NLP) Scientist
- Business Intelligence (BI) Developer
- Human-Centered Machine Learning Designer
- Software Engineer
- Software Developer
- Computational Linguist
Entry Qualification
- Candidates will be admitted on the basis of interviews and / or group discussions.
- 20% of the total seats will be reserved for SC, ST and OBC candidates.If the reserved seats are not filled within the specified period, the vacant seats will be offered to the general candidates.
Course Features
Instructor
Industry Experienced Trainer
Rating
4.9 (Google Review)
Study Mode
Offline & Online
Duration
4 month
Language
English, Bengali, Hindi
100% Job Assistance
Yes
Internship
Free & Paid
Course Price
Click to Know
Our Students Testimonials
MD Kashid Hossain
I am MD Kasid Hossain. I am a student of Oxford Global Academy of Excellence, Kolkata. Here I am doing Spoken English class. Oxford Global Academy of Excellence is a very advantage platform by spoken English, computer course and more. There sirs, madams are very Helpful. All time they Support and guide us. I always enjoy my classes.
