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Machine Learning Training



Machine Learning Training Overview

Course Duration 25 hrs
Training Options Live Online / Self-Paced / Classroom
Live Projects 4
Certification Pass Guaranteed

This Online Training course gives an in-depth view of the Machine-learning topics including working with real-time data, developing algorithms, Learning, regression of data, classification of data, etc. Python as a programming language and its use in Machine Learning and implementation.

The following professionals can look at a career in the Machine Learning space:

  • Data Scientist
  • Data Analyst
  • Engineer

Machine Learning Training Course Objectives

The course emphasizes the knowledge of Data Analytics, Business Intelligence, Software Analysis, and various packages. Comparison of R Programming and Business Analytics and other important modules is done in Machine Learning.

Anyone interested in Machine Learning and Artificial Intelligence and having an interest in programming languages can enroll for the course.

 

Machine Learning Online and Classroom 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? Case study
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
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
Need for data summary & visualization Summarising numeric data in pandas Summarising categorical data Group-wise summary of mixed data Basics of visualization with gplot & Seaborn Inferential visualization with Seaborn Visual summary of different data combinations Practice assignment
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 Case Study
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
Concept of weak learners Introduction to boosting algorithms Adaptive Boosting Extreme Gradient Boosting (XGBoost) Case Study & assignment
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 the idea of observation-based learning Distances and similarities k Nearest Neighbours (kNN) for classification Brief mathematical background on SVM/li> Regression with kNN & SVM Case Study
Need for dimensionality reduction Principal Component Analysis (PCA) Difference between PCAs and Latent Factors Factor Analysis Hierarchical, K-means & DBSCAN Clustering Case study
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
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
CA Software Technologies offers advanced Machine Learning interview questions and answers along with Machine Learning resume samples. Take a free sample practice test before appearing in the certification to improve your chances of scoring high.

Module 1: Introduction to the Course

  • Understanding Business Analytics and Data
  • Basic Operations in R Programming
  • Installation of R
  • R and its other packages

Module 2: R Programming Introduction

  • Basics of R Programming
  • R function and its relevance
  • Datatypes and functions of R Programming
  • The variables in R- Scalars, Vectors, Matrices, Factors, Detach functions in R, Data frames, List

Module 3: Data Manipulation in R

  • A dirty data set is taken up and data cleaning is undertaken on it which is resultant in a data-set that is ready for analysis.
  • The scope for data manipulation in R is:
  • Data sorting
  • Data cleaning
  • Merging of data
  • Slicing of data
  • Decoding of data
  • Data management and its application
  • Apply various functions

Module 4: Data Import Techniques

  • What is importing data
  • The importance and relevance of R- its importance which can take up data in various forms be it from a website or from a file that is in csv format.
  • The scope of data importing techniques which covers the following areas- Reading, writing and other functions

Module 5: Data Exploration and its Various Techniques

Data and its analysis and what it proves exactly are understood in Data Exploration. Understanding of the various data exploration techniques and analysis is explained in a typical Data Exploration Process. Data Exploration covers various areas:

  • Developing Graphs
  • Pie Charts
  • Line Graph
  • Histogram
  • Line Chart

Module 6:  Statistics Basics and Linear and Logistic Regression Techniques

  • Hypothesis
  • Linear and Logistic Regression
  • Classification of data
  • Data mining
  • Machine Learning and its types
  • Different types of Machine Learning- Supervised and unsupervised Machine Learning and differentiation between the two
  • The statistical measures involved
  • The various algorithms used in Machine Learning

Module 7: Analysis of Variance Technique

  • Algorithm and various aspects used in the same
  • Sentiment Analysis and its teaching

Module 8: What is Decision Trees and Random Forest

  • Concept of Decision Trees and Random Forest
  • Algorithm details discussed in detail
  • Working on Decision Trees and Random Forest
  • Distinct features of the two

Conclusion

Machine Learning is the most popular and widely used tool in recent times. Machine Learning coupled with applications and learning techniques lays the foundation for Automated Learning. A blended teaching (online and in classroom teaching approach) methodology adopted by experienced CAST trainers makes the Machine Learning Training Course valuable and easy to learn. 24/7 learning assistance is provided to the students along with placement assistance. Thus, Machine Learning certified professionals are on the path for a great and bright future ahead.

Machine Learning Training Options

For Corporates

Live Instructor Led Machine Learning Training
  • Live Presentation of theory and demonstration of features and tasks of the Denodo
  • Learn as per a daily schedule.
  • You get recordings of each training session that you attend.
  • Clarify doubts at the beginning of each training session.
  • Delivered through Goto Meeting.
  • Completely Customizable Course Content & Schedule.
  • Certification Guidance Provided.
Machine Learning Training Classroom Training
  • F2F interactive presentation of theory and demonstration of features and tasks of the Denodo
  • Learn as per full day schedule with discussions & exercises.
  • No recordings available, however you can choose self-paced video if needed.
  • Doubts Clarifications.
  • Delivered through F2F as trainer conducts the training at your facility.
  • Completely Customizable Course Content & Schedule.
  • Certification Guidance Provided.
Self Paced Learning
  • High Quality videos built by industry experts with theory and demonstration of features and tasks of the Denodo
  • Learn at your Convenience.
  • You get pre-defined recordings.
  • Delivered through LMS.
  • Fixed Course Content.
  • Certification Guidance Provided.

Machine Learning Training Upcoming Batches

Mon-28-2022

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Tue-29-2022

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Wed-30-2022

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Thu-01-2022

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Fri-02-2022

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Sat-03-2022

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Sun-04-2022

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Sat-10-2022

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Sun-11-2022

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Sat-17-2022

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Sun-18-2022

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Sat-24-2022

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Sun-25-2022

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What our Customer say's

"Great explanation of concepts through live examples, this helped me to link the topics and understand the connect between various topics of Tibco Spotfire Admin. Excellent. Great learning experience.. Thanks a lot CAST!!"

Mr. Chandra

Certified Student

(4.5)

"Thank You for the sessions that helped me gaining knowledge in Spotfire. Trainers experience helped me to get detailed information regarding the key concepts and challenging tasks in real time. Thanks once again"

Mr. Arun

Certified Student

(4.5)

"The trainer of the casoftwaretechnologies.com is top rated customer provided the more useful information In Tibco Spotfire Admin Training than the normal which helped me to improve my skills.. Thanks to CA software technologies"

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Certified Student

(4)

Machine Learning Training Certification !

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Features

Online guidance session or Instructor led course delivery online

24*7 delivery of learning through live lectures and demonstrations by industry experts. Weekend class: 8 sessions of 1 to 4+ hours each in Online Mentorship Mode

Hands-on experience with Real-time scenarios

End to end training with real-time practical exposure. Get to experience on projects using key progressive concepts.

Gauge learners understanding

Formative evaluation of the trainees at the end of each class.

Unlimited Online Access

You get Lifetime Unlimited Online Training Videos, presentations, installation guide to enhance your knowledge

7×24 technical support expertise

24/7/365 technical support with powerful ticket tracking system for life

Certification

Stay ahead of the game with our certificate after course completion

Assessments

Each class will be followed by a test to assess your learning.

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Experts Available 24 x 7

+91 912 110 4115
info@casoftwaretechnologies.com

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+91 912 110 4115
Experts Available 24 x 7