Machine Learning Training

  • (4.8)
  • 236 Ratings
  • Learners : 261
Try Live Demo

Trusted By Companies Worldwide & 3,50,850+ Learners

Machine Learning Course Overview

By taking Machine learning (ML) training from Tekslate, you’ll become an expert in working with Artificial neural networks. This course enables you to gain in-depth knowledge of ML concepts and techniques. It will help you to develop skills on supervised and unsupervised learning and provides hands-on experience in modeling to develop algorithms and mathematical and heuristic aspects. Our curriculum is designed by industry experts based on real-time scenarios. You will get hands-on experience in ML by working on various real-time applications.  
Course Duration 30 hrs
Live Projects 2
Next Batch 21 Nov, 2019
23 Nov, 2019
26 Nov, 2019

Machine Learning Course Curriculum

  • 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?
     
  • 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
     
  • 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
     
  • Need for data summary & visualization
  • Summarising numeric data in pandas
  • Summarising categorical data
  • Group-wise summary of mixed data
  • Basics of visualization with ggplot & Seaborn
  • Inferential visualization with Seaborn
  • Visual summary of different data combinations
     
  • Introduction to NumPy arrays, functions & properties
  • Introduction to Pandas & data frames
  • Importing and exporting external data in Python
  • Feature engineering using Python
     
  • Linear Regression
  • Regularisation of Generalised Linear Models
  • Ridge and Lasso Regression
  • Logistic Regression
  • Methods of threshold determination and performance measures for classification score models
     
  • 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
     
  • The concept of weak learners
  • Introduction to boosting algorithms
  • Adaptive Boosting
  • Extreme Gradient Boosting (XGBoost)
     
  • 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
     
  • Introduction to idea of observation-based learning
  • Distances and similarities
  • k Nearest Neighbours (kNN) for classification
  • Brief mathematical background on SVM/li>
  • Regression with kNN & SVM
     
  • Need for dimensionality reduction
  • Principal Component Analysis (PCA)
  • Difference between PCAs and Latent Factors
  • Factor Analysis
  • Hierarchical, K-means & DBSCAN Clustering
     
  • 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
     
  • Need and Importance of Version Control
  • Setting up git and GitHub accounts on a 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
     
For Individuals
For Corporates

Machine Learning Upcoming Batches

  • Weekend

    21 Nov - 21 Dec

    7:00 AM IST
  • Weekday

    23 Nov - 23 Dec

    7:00 AM IST
  • Weekend

    26 Nov - 26 Dec

    7:00 AM IST
  • Weekday

    28 Nov - 28 Dec

    7:00 AM IST
  • Weekend

    1 Dec - 31 Dec

    7:00 AM IST
  • Weekday

    5 Dec - 04 Jan

    7:00 AM IST
  • Schedules Doesn't Suit You ?

    Our Team can set up a batch at your convinient time.

    Let us know

    Machine Learning Course Objectives

    By the end of Machine Learning training, you will be able to:

    • Understand what machine learning is with the help of real-time examples.
    • Master the concepts of supervised, unsupervised and reinforcement learning.
    • Gain practical knowledge of principles, algorithms, and applications of machine learning.
    • Acquire knowledge of the mathematical and heuristic aspects of machine learning.
    • Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes.
    • Model a wide variety of robust machine learning algorithms including deep learning.
       
    • According to a recent survey, it is estimated that 64% of enterprises are investing in machine learning, creating huge job opportunities around the globe.
    • Machine learning jobs are in high demand and top MNCs are hiring certified machine learning professionals worldwide.
    • The average salary of a certified machine learning professional is around $103.875 USD per annum.
       
    • Data Analysts
    • AI and IoT developers
    • Programmers
    • Aspirants willing to build their career in the prospective field.
       

    The following are the prerequisites for learning Machine Learning course:

    • Understanding of data science
    • Passion for new technologies

    The following job roles will get benefited by taking up this course:

    • Professionals in analytics
    • Data scientists
    • E-commerce site developers

    The tutor will take care of handling the projects. We will provide two real-time projects with a highly-skilled guide who can assist you throughout the project.
     

    Have More Questions

    Contact us

    Machine Learning Course FAQ's

    Have questions? We’ve got the answers. Get the details on how you can grow in this course.

    We have a strong team of professions who are experts in their fields. Our trainers are highly supportive and render a friendly working environment to the students positively stimulating their growth. 
     

    We will share you the missed session from our recordings. We at Tekslate maintains a recorded copy of each live course you undergo.
     

    Our Trainers will provide the student with the Server Access ensuring practical real-time experience and training with all the utilities required for the in-depth understanding of the course.
     

    We provide all the training sessions LIVE using either GoToMeeting or WebEx, thus promoting one-on-one trainer student Interaction.
     

    Live training uncovers distinct benefits as they are mighty to reach your desired audience converting your prospects into customers in less time. Pre-recorded videos offer plenty of advantages for entrepreneurs to educate entertain and inspire your audience as long as you want.
     

    You can contact our Tekslate support team, or you can send an email to info@tekslate.com for your queries.
     

    Yes. We provide the course materials available after course completion.
     

    There exist some discounts for weekend batches and group participants if the joiners are more than 2.
     

    If you are enrolled in classes and have paid fees but want to cancel the registration for any reason, we will attain you in 48 hours will be processed within 30 days of prior request.
     

    Have More Questions. Reach our Support Team

    Contact us

    Join a Free Machine Learning Demo Session

    See if this course is a fit for you by joining us for an online info session. You’ll meet our team, get an overview of the curriculum and course objectives, and learn about the benefits of being a student at Tekslate

    Attend a Demo Session | Meet the Expert Who Can Kickstart Your Career in Machine Learning

    By providing us with your details, We wont spam your inbox.