Machine Learning Certification Training Course
The world is becoming digital and to aid it to grow successfully machine learning greatly contributes. The aim of this online machine learning course offered by Staragile is to let you explore all the ML concepts which is the most important part of artificial intelligence. The course covers the overview of machine learning concepts and how to work with real-time data as well as the right way to develop algorithms, regression analysis, and time series modeling.
Machine Learning Course
Gain expertise with 25+ hands-on exercises - 4 real-life industry projects with integrated labs
Gain expertise with 25+ hands-on exercises - Dedicated mentoring sessions from industry experts
- 44 hours of instructor-led training with certification
Machine Learning Course Content
- Learning Objectives
- Emergence of Artificial Intelligence
- Artificial Intelligence in Practice
- Sci-Fi Movies with the Concept of AI
- Recommender Systems
- Relationship between Artificial Intelligence, Machine Learning
- Definition and Features of Machine Learning
- Machine Learning Approaches
- Machine Learning Techniques
- Data Exploration Loading Files: Part A
- Data Exploration Loading Files: Part B
- Demo: Importing and Storing Data
- Practice: Automobile Data Exploration - A
- Data Exploration Techniques: Part A
- Data Exploration Techniques: Part B
- Seaborn
- Demo: Correlation Analysis
- Practice: Automobile Data Exploration - B
- Data Wrangling
- Missing Values in a Dataset
- Outlier Values in a Dataset
- Demo: Outlier and Missing Value Treatment
- Practice: Data Exploration - C
- Data Manipulation
- Functionalities of Data Object in Python: Part A
- Functionalities of Data Object in Python: Part B
- Different Types of Joins
- Typecasting
- Demo: Labor Hours Comparison
- Practice: Data Manipulation
- Supervised Learning
- Supervised Learning- Real-Life Scenario
- Understanding the Algorithm
- Supervised Learning Flow
- Types of Supervised Learning: Part A
- Types of Supervised Learning: Part B
- Types of Classification Algorithms
- Types of Regression Algorithms: Part A
- Regression Use Case
- Accuracy Metrics
- Cost Function
- Evaluating Coefficients
- Demo: Linear Regression
- Challenges in Prediction
- Types of Regression Algorithms: Part B
- Logistic Regression: Part A
- Logistic Regression: Part B
- Sigmoid Probability
- Accuracy Matrix
- Demo: Survival of Titanic Passengers
- Practice: Iris Species
- Knowledge Check
- Feature Selection
- Regression
- Factor Analysis
- Factor Analysis Process
- Principal Component Analysis (PCA)
- First Principal Component
- Eigenvalues and PCA
- Demo: Feature Reduction
- Practice: PCA Transformation
- Linear Discriminant Analysis
- Maximum Separable Line
- Find Maximum Separable Line
- Demo: Labeled Feature Reduction
- Practice: LDA Transformation
- Learning Objectives
- Overview of Classification
- Classification: A Supervised Learning Algorithm
- Use Cases of Classification
- Classification Algorithms
- Decision Tree Classifier
- Decision Tree Examples
- Decision Tree Formation
- Choosing the Classifier
- Overfitting of Decision Trees
- Random Forest Classifier- Bagging and Bootstrapping
- Performance Measures: Confusion Matrix
- Performance Measures: Cost Matrix
- Horse Survival
- Practice: Loan Risk Analysis
- Naive Bayes Classifier
- Steps to Calculate Posterior Probability: Part A
- Steps to Calculate Posterior Probability: Part B
- Support Vector Machines : Classification Margin
- Linear SVM : Mathematical Representation
- Non-linear SVMs
- The Kernel Trick
- Voice Classification
- Overview
- Example and Applications of Unsupervised Learning
- Clustering
- Hierarchical Clustering
- Hierarchical Clustering Example
- Clustering Animals
- Practice: Customer Segmentation
- K-means Clustering
- Optimal Number of Clusters
- Cluster Based Incentivization
- Practice: Image Segmentation
- Clustering Image Data
- Overview of Time Series Modeling
- Time Series Pattern Types: Part A
- Time Series Pattern Types: Part B
- White Noise
- Stationarity
- Removal of Non-Stationarity
- Time Series Models: Part A
- Time Series Models: Part B
- Time Series Models: Part C
- Steps in Time Series Forecasting
- IMF Commodity Price Forecast
- Ensemble Learning
- Ensemble Learning Methods: Part A
- Ensemble Learning Methods: Part B
- Working of AdaBoost
- AdaBoost Algorithm and Flowchart
- Gradient Boosting
- XGBoost
- XGBoost Parameters: Part A
- XGBoost Parameters: Part B
- Practice: Linearly Separable Species
- Model Selection
- Common Splitting Strategies
- Cross Validation
- Practice: Model Selection
- Tuning Classifier Model with XGBoost
- Introduction
- Purposes of Recommender Systems
- Paradigms of Recommender Systems
- Collaborative Filtering: Part A
- Collaborative Filtering: Part B
- Association Rule Mining
- Association Rule Mining: Market Basket Analysis
- Association Rule Generation: Apriori Algorithm
- Apriori Algorithm Example: Part A
- Apriori Algorithm Example: Part B
- Apriori Algorithm: Rule Selection
- User-Movie Recommendation Model
- Practice: Movie-Movie recommendation
- Book Rental Recommendation
- Overview of Text Mining
- Significance of Text Mining
- Applications of Text Mining
- Natural Language ToolKit Library
- Text Extraction and Preprocessing: Tokenization
- Text Extraction and Preprocessing: N-grams
- Text Extraction and Preprocessing: Stop Word Removal
- Text Extraction and Preprocessing: Stemming
- Text Extraction and Preprocessing: Lemmatization
- Text Extraction and Preprocessing: POS Tagging
- Text Extraction and Preprocessing: Named Entity Recognition
- NLP Process Workflow
- Structuring Sentences: Syntax
- Rendering Syntax Trees
- Structuring Sentences: Chunking and Chunk Parsing
- NP and VP Chunk and Parser
- Structuring Sentences: Chinking
- Context-Free Grammar (CFG)
- Demo: Structuring Sentences
- Project Highlights
- Uber Fare Prediction
- Amazon - Employee Access
Machine Learning Course Overview
Staragile’s ML online certification training using Python helps the audience to understand machine learning concepts and thus draw predictions from the data. This training program is designed to offer a deeper understanding of machine learning along with all the associated mechanisms. Every data scientist must know what machine learning is and how to implement it using Python. Also, the course curriculum includes teaching an important aspect of AI called reinforcement learning. The course includes a live demo, hands-on exercises, real-life projects, case studies, and practicals.
You will know about time series modeling, Kernel SVM, Decision tree, Naïve Bayes, KMeans clustering, random forest classifiers, fundamentals of deep learning, boosting, and bagging techniques.
Machine Learning Certificate
Machine Learning Certification and Training FAQ's
The training includes lectures, study materials, access to recorded videos, mock tests, practical sessions, and projects.
We also provide placement assistance and not guaranteed placement assurance. We provide you with contacts and being part of our community will allow you to exchange information with our alumni for a better placement opportunity.
At the same time, we also collect your resume in our database to refer to jobs.
Some people think that machine learning is all about math, but it is more about coding, data analysis, and algorithms.
It is not essential to know Python to do machine learning, but it can be helpful to learn the basics of the language.
Machine learning does not require coding, but it can be enhanced with coding languages such as Prolog, Lisp, and R for more efficient results.
Machine learning offers many opportunities for career growth. This field of study is full of opportunities for a bright future with great salaries.
Machine learning is the subject wherein the machine learns by examples from the data sets similar to what humans do that is learned by examples. ML is part of artificial intelligence that makes the machine imitate work just like humans. ML consists of subjects such as Natural language processing, Chatbots, Personal assistants, Artificial Neural network and Vision, and image processing. All these form the basis for machine and human communication and other work done by machines.
- Make machine work for us by learning
- Imitate humans in actions
- Able to make error-free work
- Able to make machines do the work where humans cannot do
- Make machines do the work that is repetitive and monotonous
- Make machine communicate with humans to solve the problems
- Learning machine learning offers high salary and growth prospects
- Learning machine learning encompasses the work of training the machines
- Learning ML offers challenging jobs and taxing complex work of making machines do things.
Yes, it is a great idea for freshers to attend a training course to get placed in the right job. Given the current market scenario and the pandemic, it is a must that freshers should register for a machine learning course that has a good future scope.
Register with Stragile and we will walk you through the process to make you a machine learning engineer with our well-organized machine learning online course curriculum.
The purpose of the machine learning online course is to provide a detailed idea about the following concepts and make you a data scientist with machine learning skills.
- First things first, the course begins with providing an overview of the roles and responsibilities of a machine learning engineer
- Detail about time series modeling
- Provide experience to work with real-time data
- How to automate the data analysis process using Python
- Explain all the tools for predictive modeling
- Provide ways to implement a machine learning algorithm
- You will understand data science
- How to extract data, wrangle data and visualize data
- How to use Python and do better predictive modeling
- Supervised, unsupervised learning
- Regression analysis
- Recommendation systems
- Association rules
- Time series modeling
- Reinforcement learning
- Boosting and bagging techniques
- Every developer who wants to become a machine learning engineer can attend the training and start applying their programming language to automate the system in data analysis
- Analytics manager
- Information Architects
- Business analyst
- Even freshers can attend the course to start their journey in machine learning and artificial intelligence
- Chatbot that answers the customer queries
- Charge predictor for booking systems
- Knowledge of python programming language or at least some experience in coding using any object-oriented programming language
- Understanding of data analysis tools like SAS or working knowledge of R programming is a plus
However, anyone can apply for the course as the course covers all the basics, and thus becoming a machine learning engineer needs a college graduate degree and flair to learn.
As per the data collected from Glassdoor, Payscale, and Indeed sites, the following is the average base salary of Machine learning professionals in Bangalore
- Entry-level professionals – 5 LPA
- 1 – 4 years experience – 6 – 7 LPA
- 5 – 9 years experience – 10 -12 LPA
- Senior professionals with 10+ years experience – 18 – 25 LPA
- Amazon
- Airbnb
- Accenture
- Spotify
- Netflix
- Walmart
- IBM
- Deloitte
- Capgemini
These are the few companies that constantly look for machine learning talents across the year. There are also startup companies which provide data prediction and analysis hire machine learning and data scientist in Bangalore. Close to 380 startups are there in Bangalore according to Crunchbase and Angel listing offering a greater job opportunity.
Bangalore city has more than 50% of the product company's Indian headquarters and there is a huge demand for machine learning jobs. Online learning has become a common practice in recent years and the Covid19 Pandemic has made it a need of the hour. Thus irrespective of the areas in Bangalore machine learning online courses are conducted across places that can be attended from across anywhere online.
Visit our website to contact us via email, chat, or submit a query form. Call us to talk to our customer service representative.
We will provide you with guidelines to use Jupyter Notebook which is an open source web application that makes creating and sharing documents with live codes, equations, narrative text, and visualizations.
Also, we will teach you to stay connected with us using the Cloud LAB environment. We always extend support through our 24/7 support system.
- 32-bit or 64-bit processor
- Windows or Mac OS
- Minimum of 8GB RAM
- Graphics processing unit – NVIDIA GeForce GTX 960
- Install Jupyter Notebook
- Work on the live codes and equations
- Share via Cloud Lab
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There are 2 ways you can attend the training. If you want to connect with the trainer, interact and ask doubts then choose live virtual online classroom training. You can use the login Id given at the time of registration and join the class at the mutually agreed time and listen to live lectures.
We will provide you with access to recorded videos of every live lecture after the sessions and thus can make use of it to get hold of the missed sessions. Get in touch with your trainer for any doubts during business hours.
Our hiring process is fool-proof to assess the skills of the instructor. We do a background check of their industry and training experience. They also go through an interview process which includes many rounds to express their knowledge in machine learning. Industry experts with more than a decade of teaching experience are our base criteria to call trainers for our selection process.
We have a team of experts who extend their support to train you with a machine learning course. They guide you and help you clear the test, complete the project, and get certified. They provide you with inspirational ideas and review your project before approving your certification. They are your mentor available during business hours for clarifying your subject related doubts.
Login to your system from home. Join the online class with Staragile. Meet your trainer and other participants virtually. Listen to lectures, ask doubts, and exchange views. A classroom with participants from their respective places will still stay connected.
Our team provides an answer to your queries via email, chat, and phone. You can follow the steps given below and reach us.
- Visit Staragile Contact us page. Submit the form
- Send an email with your query to trainings@staragile.com
- Call us
- Click on Drop a Query
However, for immediate reply chat with our Chatbot and to know how just visit www.staragile.com and you will see a pop-up waiting to help you.
The cost for SAS training would be approximately Rs19,999. However, reach StarAgile team to avail discounts.
- Visit our website
- Choose Data Science Courses
- Select the course you want to enroll for
- Decide on the mode of training
- Based on that you will get to know the fees
- Pay using a credit card, debit card, Paypal, NEFT
- Choose your training slots
- Attend the class online
- You can learn machine learning concepts from our expert trainers
- Get access to recorded videos
- Understand real-time data and work on practicals
- Attend demo classes to get more knowledge
- Take a mock test to prepare for the exam
- Complete project get it to review by experts
- Collect your certificate
- Avail our placement assistance to get placed
- Stay in touch with us for any future support
Machine Learning Certification & Exam FAQ's
Yes, the mock test is part of the machine learning training with 20 MCQs and you will have 25 minutes to complete the test. You can take this test multiple times to answer different questions and master machine learning concepts.
- Choose the training mode with Staragile Live virtual or self-learning with pre-recorded videos
- Make payment
- Attend the class
- Complete project and get certified
With the boom in technology, there is a huge demand for machine learning professionals as AI is dominating the market across industries. If you wish to kick start your career in machine learning, then enroll for a machine learning training with Staragile and get certified. The experience you gain in the entire training will provide you with skills, confidence, and experience to apply for ML jobs.
Staragile issues the machine learning certification for all the participants who attend the course completes the project and qualify as a machine learning engineer. This certificate is valid for a lifetime.
Some common requirements include a bachelor’s degree in mathematics and statistics, computer science, and experience with programming languages such as Python or R.
While machine learning is often seen as a complex and difficult field with the right tools and resources, it can be mastered by anyone.
Machine Learning Course
Several jobs are available to those who have learned machine learning. These jobs include data scientist, machine learning engineer, and business intelligence developer.
Machine learning is growing in demand as businesses strive to stay competitive in a data-driven world.
Distinctions and Achievements
Machine Learning Course
You will know about time series modeling, Kernel SVM, Decision tree, Naïve Bayes, KMeans clustering, random forest classifiers, fundamentals of deep learning, boosting, and bagging techniques.
Comprehensive Training Solutions for Enterprises
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