Machine Learning Online Training

The Machine Learning Online Training at Course Dx will provide you the best knowledge on Machine learning basics, algorithms, ML techniques, Data mining, etc. with live experts. Learning Online Machine Learning makes you a master in this subject that includes predictive analysis, neural networks concept, types of Machine learning, etc. Our best Machine Learning Training module will provide you a way to become certified in Machine Learning technology. So, join hands with Course Dx for accepting new challenges and make the best solutions through the Machine Learning Certification Course. Learn Machine Learning Online basics and other features to make you an expert in the Machine Learning techniques & tools to deal with real-time tasks. Course Dx provides the best Machine Learning Course Online, where you will come to know how Machine Learning is useful in different fields & businesses. The best Online Machine Learning Course with Course Dx will help you to get your training easily with the latest skills and will make you certified and skillful in the ML platform.

Choose The Training That's Best For You

LIVE ONLINE TRAINING

  • High-quality content created by industry experts
  • Lifetime access to high-quality self-paced learning and live online class recordings
  • Flexible, affordable options
  • Get complete certification guidance
  • 24×7 assistance and support
  • Attend a ML Online Course free demo before signing up

CORPORATE TRAINING

  • Self-Paced / Live Online training options
  • Flexible, affordable options
  • Learn as per full day schedule and/or flexible timings
  • Customize your own course content based on your project requirements
  • Get complete certification guidance
  • 24×7 assistance and support

Machine Learning Online Training Upcoming Batches

Weekday

20,SEP 2020
Time: 7:00PM IST

Weekend

20,SEP 2020
Time: 7:00PM IST

FastTrack

20,SEP 2020
Time: 7:00PM IST

Don’t find suitable time ?

₹ 23500

SELF-PACED LEARNING

  • 25 hours high-quality video
  • 2 projects
  • 20 downloadable resource
  • Lifetime access and 24×7 support
  • Access on your computer or mobile

1
Introduction to Data Science
  • What is data science and why is it so important?
  • Applications of data science
  • Various data science tools
  • Data Science project methodology
  • Tool of choice-Python: what & why?
  • Case study
2
Introduction to Python
  • Installation of Python framework and packages: Anaconda & pip
  • Writing/Running python programs using Spyder Command Prompt
  • Working with Jupyter notebooks
  • Creating Python variables
  • Numeric , string and logical operations
  • Data containers : Lists , Dictionaries, Tuples & sets
  • Practice assignment
3
Iterative Operations & Functions in Python
  • Writing for loops in Python
  • While loops and conditional blocks
  • List/Dictionary comprehensions with loops
  • Writing your own functions in Python
  • Writing your own classes and functions
  • Practice assignment
4
Data Summary & Visualization in Python
  • Need for data summary & visualization
  • Summarizing numeric data in pandas
  • Summarizing categorical data
  • Group wise summary of mixed data
  • Basics of visualization with ggplot & Seaborn
  • Inferential visualization with Seaborn
  • Visual summary of different data combinations
  • Practice assignment
5
Data Handling in Python using NumPy & Pandas
  • Introduction to NumPy arrays, functions & properties
  • Introduction to Pandas & data frames
  • Importing and exporting external data in Python
  • Feature engineering using Python
6
Generalized Linear Models in Python
  • Linear Regression
  • Regularization of Generalized Linear Models
  • Ridge and Lasso Regression
  • Logistic Regression
  • Methods of threshold determination and performance measures for classification score models
  • Case Study
7
Tree Models using Python
  • Introduction to decision trees
  • Tuning tree size with cross validation
  • Introduction to bagging algorithm
  • Random Forests
  • Grid search and randomized grid search
  • ExtraTrees (Extremely Randomised Trees)
  • Partial dependence plots
  • Case Study & Assignment
8
Boosting Algorithms using Python
  • Concept of weak learners
  • Introduction to boosting algorithms
  • Adaptive Boosting
  • Extreme Gradient Boosting (XGBoost)
  • Case Study & assignment
9
Machine Learning Basics
  • Converting business problems to data problems
  • Understanding supervised and unsupervised learning with examples
  • Understanding biases associated with any machine learning algorithm
  • Ways of reducing bias and increasing generalization capabilities
  • Drivers of machine learning algorithms
  • Cost functions
  • Brief introduction to gradient descent
  • Importance of model validation
  • Methods of model validation
  • Cross validation & average error
10
Support Vector Machines (SVM) & kNN in Python
  • Introduction to idea of observation based learning
  • Distances and similarities
  • k Nearest Neighbors (kNN) for classification
  • Brief mathematical background on SVM/li>
  • Regression with kNN & SVM
  • Case Study
11
Unsupervised learning in Python
  • Need for dimensionality reduction
  • Principal Component Analysis (PCA)
  • Difference between PCAs and Latent Factors
  • Factor Analysis
  • Hierarchical, K-means & DBSCAN Clustering
  • Case study
12
Text Mining in Python
  • Gathering text data using web scraping with urllib
  • Processing raw web data with BeautifulSoup
  • Interacting with Google search using urllib with custom user agent
  • Collecting twitter data with Twitter API
  • Naive Bayes Algorithm
  • Feature Engineering with text data
  • Sentiment analysis
  • Case study
13
Version Control using Git and Interactive Data Products
  • Need and Importance of Version Control
  • Setting up git and github accounts on local machine
  • Creating and uploading GitHub Repos
  • Push and pull requests with GitHub App
  • Merging and forking projects
  • Introduction to Bokeh charts and plotting
  • Examples of static and interactive data products
  • Case study
Yes, you can schedule your Machine Learning Online Training in all Time Zones and we also offer training classes with the US, UK, Australia, & Europe based trainers on Weekends and Weekdays.
Our expert trainer will provide the server access to the Machine Learning Certification Course aspirants. Moreover, you will get practical training on Machine learning with live sessions that cover all your training needs about the course along with the Project.
Even if you have missed a class for the Machine Learning Online Course, then you can watch it as a recorded video within your LMS or attend the same in another live batch.
Our Machine Learning Course trainer is a certified consultant and at present, he is working on a project within this technology and he is experienced too.
Yes, we will help you in getting certified in the best Machine Learning Training and we promise you that after completing our online training program, you will get a certificate in the technology for sure.
Our expert Machine Learning Online Course trainer will explain to you the subject and project work in detail on the software itself with live training. Each training batch of candidates is a software team within our Machine learning training program and project work is offered to them. After the completion of the project work in Machine Learning, the training will be complete for the students. So, the trainees can feel the real-time IT company environment during our Machine Learning online training program, where our trainer is a Team Leader.

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Lectures: 13