Corporate Introduction to Machine Learning Training Course

Name: Introduction to Machine Learning Training
Availability: InStock

Edstellar's Introduction to Machine Learning instructor-led training course enables teams to develop predictive models, automate repetitive tasks, and derive actionable insights from vast data. Empower your team with the knowledge and techniques to apply machine learning algorithms effectively and drive innovation with our comprehensive training.

Duration

40 - 48 hrs

Delivery Type

Instructor-led Group Training
(Virtual / On-site / Off-site)

Training Available in

10 Languages

Multiple Locations

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About Learning Outcomes Key Benefits Course Outline Target Audience Training Modes Certificate Trainers Request a Training Quote

Drive Team Excellence with Introduction to Machine Learning Corporate Training

Machine learning is a branch of artificial intelligence that focuses on developing algorithms and statistical models to enable computers to learn from and make predictions or decisions based on data, without being explicitly programmed. It's crucial for organizations because it empowers them to extract valuable insights from large datasets, automate processes, enhance decision-making, and personalize experiences. Training in machine learning involves iteratively feeding data into algorithms to adjust and improve their performance in making accurate predictions or decisions.

Introduction to Machine Learning instructor-led training course provided by Edstellar can be customized to meet team requirements. The virtual/onsite Introduction to Machine Learning training course led by expert trainers ensures professionals gain a comprehensive coverage of machine learning fundamentals, hands-on experience with popular algorithms, and practical insights into real-world applications.

Get Customized Expert-led Training for Your Teams

Customized Training Delivery

Scale Your Training: Small to Large Teams

In-person Onsite, Live Virtual or Hybrid Training Modes

Plan from 2000+ Industry-ready Training Programs

Experience Hands-On Learning from Industry Experts

Delivery Capability Across 100+ Countries & 10+ Languages

Skills Your Employees Will Gain

These are the core, hands-on capabilities your team builds during the program.

Data Analysis
Data Analysis is the process of inspecting, cleansing, and modeling data to discover useful information. This skill is important for roles like data scientist and business analyst, as it drives informed decision-making and strategy development.
Statistical Modeling
Statistical Modeling involves using mathematical techniques to analyze data and make predictions. This skill is important for data analysts and researchers to derive insights, inform decisions, and optimize processes.
Algorithm Design
Algorithm Design is the process of creating efficient, step-by-step procedures for solving problems. This skill is important for software developers and data scientists, as it enables them to optimize solutions, enhance performance, and tackle complex challenges effectively.
Programming Skills
Programming Skills involve writing, testing, and maintaining code to create software applications. This skill is important for developers, data analysts, and engineers to innovate and solve complex problems efficiently.
Feature Engineering
Feature Engineering is the process of selecting, modifying, or creating features from raw data to improve model performance. This skill is important for data scientists and machine learning engineers as it directly impacts model accuracy and effectiveness.
Model Evaluation
Model Evaluation is the process of assessing a machine learning model's performance using metrics like accuracy and precision. this skill is important for data scientists and machine learning engineers to ensure models are effective and reliable in real-world applications.

What Your Team Will Achieve After This Training

Differentiate between supervised and unsupervised learning paradigms, along with their common algorithms
Apply unsupervised learning methods like k-means clustering to uncover hidden patterns and group similar data points
Employ logistic regression to categorize data points into predefined classes and interpret the model's output probabilities
Choose appropriate evaluation metrics (accuracy, precision, recall) to assess the performance of a machine learning model
Build and utilize linear regression models to solve prediction problems, understanding the impact of regularization techniques
Articulate the core concepts of machine learning and its significance in various industries like healthcare, finance, and marketing
Recognize the different stages involved in a typical machine learning project, including data preparation, model selection, and evaluation
Apply data cleaning techniques to handle missing values and prepare data for model training using methods like scaling and normalization

Topics & Program Outline

The curriculum is organized into focused modules built by industry experts and delivered virtually or on-premise. Interactive sessions reflect the evolving demands of the workplace, keeping the learning both relevant and practical.

Introduction to Machine Learning

What is machine learning
- Definition and basic concepts
- Importance in today's world
Popular applications of machine learning
- Healthcare, finance, marketing, etc.
- Real-world examples
Lifecycle of a machine learning project
- Steps in a typical ML project
- Project management and best practices
Introduction to supervised learning
- Definition and examples
- Key supervised learning algorithms
Introduction to unsupervised learning
- Definition and examples
- Key unsupervised learning algorithms

Data Exploration

Importance of data exploration
- Role in the machine learning process
- Impact on model performance
Data preprocessing techniques
- Data cleaning and handling missing values
- Feature scaling and normalization
Data visualization methods
- Types of visualizations
- Tools and libraries for data visualization

Evaluation Metrics

Understanding hypothesis testing
- Null and alternative hypotheses
- Types of errors in hypothesis testing
Common evaluation metrics in machine learning
- Accuracy, precision, recall, F1 score
- ROC curve and AUC

Linear Regression

Introduction to regression
- Definition and basic concepts
- Difference between regression and classification
Types of regression
- Linear regression
- Polynomial regression
Regularization techniques
- Ridge regression
- LASSO regression

Classification

Overview of classification algorithms
- Definition and basic concepts
- Types of classification (binary, multi-class)
Logistic regression in classification
- Sigmoid function and probability estimation
- Model evaluation metrics
Decision trees in classification
- Building decision trees
- Tree pruning and optimization
Random forests in classification
- Ensemble learning
- Advantages and applications

Unsupervised Learning

Introduction to unsupervised learning
- Definition and basic concepts
- Difference between supervised and unsupervised learning
Clustering methods
- K-means clustering
- Hierarchical clustering
Association rules and their applications
- Apriori algorithm
- Market basket analysis

Who Should Attend?

This program suits professionals at many levels across the organization, including:

Data Scientists
Machine Learning Engineers
Data Analysts
Software Developers
Research Scientists
AI Engineers
Statisticians
Quantitative Analysts
Product Managers
Research Analysts
BI Analysts
Data Wranglers

What are the Prerequisites?

Professionals with a basic coding experience in any programming language and some exposure to Python and its libraries can take up the Introduction to Machine Learning training course.

Request a Quote for your Corporate Training Requirements

Delivering Training for Organizations across 100 Countries and 10+ Languages

Choose the Format That Fits Your Team

We design training your teams actually engage with, and deliver it the way that suits you best. Through a vetted global trainer network, Edstellar runs sessions in 10+ languages with consistent quality anywhere.

Virtual Introduction to Machine Learning Training

Virtual / online: expert-led live sessions delivered anywhere, with consistency and easy scheduling.

We deliver anywhere worldwide

Standardized content for consistent outcomes

Join from own workspace, no travel

We scale to large groups across sites

Interactive tools keep remote learners engaged

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On-site Introduction to Machine Learning Training

On-site (in-house): immersive, instructor-led learning at your office.

Our trainers run face-to-face at your office

We tailor setup/content to your workplace and tools

Group exercises drive collaboration

Live demos + hands-on practice

Direct trainer access to clarify doubts

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Off-site Introduction to Machine Learning Training

Off-site: focused, instructor-led group learning away from everyday workplace distractions.

We host your teams at a venue of your preferred choice

Built-in group activities for bonding

Full uninterrupted schedule for focus/retention

Boosts morale and signals commitment

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What Sets Edstellar Apart

Experienced Trainers

Our trainers are drawn from a vetted global network and bring years of industry expertise, keeping every session practical and impactful.

Proven Quality

With a strong global track record, Edstellar is known for quality and engaging delivery.

Industry-Relevant Curriculum

Our programs are built by experts to match the demands of today's industry.

Fully Customizable

Every program can be tailored to your organization's goals.

Comprehensive Support

We provide pre- and post-session support for a complete learning experience.

Global Multi-Location & Multilingual Training Delivery

We deliver in multiple languages to support diverse global teams.

Hear from Organizations We've Trained

"Attending the Introduction to Machine Learning training was transformational for my professional development. As a Principal Analytics Architect, the deep dive into advanced methodologies gave me the confidence to tackle of practical simulations were immediately applicable to my work. My productivity and technical capabilities have increased dramatically since applying these concepts. This course has become foundational to my continued success.”

Ashley Bradley

Principal Analytics Architect,

AI Solutions Platform Provider

"This Introduction to Machine Learning course was precisely what I needed to design robust technical mastery architectures. The hands-on approach to expert-led workshops and seamless integration with real-world case projects using advanced techniques from this training. We've successfully expanded our service portfolio based on these enhanced capabilities. The comprehensive curriculum has elevated my solution delivery capabilities significantly.”

Manfred Richter

Senior Machine Learning Engineer,

Predictive Analytics Firm

"As a Senior Database Administrator overseeing technical mastery initiatives, the Introduction to Machine Learning training significantly elevated our team's capabilities. The course expertly covered strategic frameworks, hands-on effectiveness. Our team has automated eighteen critical business processes, reducing manual effort by 70%. Our department has achieved remarkable improvements, demonstrating this course's lasting organizational impact.”

Krishnan David

Senior Database Administrator,

ML Model Development Platform

“Edstellar’s IT & Technical training programs have been instrumental in strengthening our engineering teams and building future-ready capabilities. The hands-on approach, practical cloud scenarios, and expert guidance helped our teams improve technical depth, problem-solving skills, and execution across multiple projects. We’re excited to extend more of these impactful programs to other business units.”

Aditi Rao

L&D Head,

A Global Technology Company

Recognition That Motivates Your Team

Upon successful completion of the training course offered by Edstellar, employees receive a course completion certificate, symbolizing their dedication to ongoing learning and professional development.

This certificate validates the employee's acquired skills and is a powerful motivator, inspiring them to enhance their expertise further and contribute effectively to organizational success.

We have Expert Trainers to Meet Your Introduction to Machine Learning Training Needs

The instructor-led training is conducted by certified trainers with extensive expertise in the field. Participants will benefit from the instructor's vast knowledge, gaining valuable insights and practical skills essential for success in Access practices.

Mohammed

Bengaluru, India

Trainer since

November 1, 2001

Chandan

Bengaluru, India

Trainer since

April 1, 2011

Arijeet

Noida, India

Trainer since

July 1, 2017

Corporate Introduction to Machine Learning Training Course

Drive Team Excellence with Introduction to Machine Learning Corporate Training

Skills Your Employees Will Gain

What Your Team Will Achieve After This Training

Topics & Program Outline

Introduction to Machine Learning

Data Exploration

Evaluation Metrics

Linear Regression

Classification

Unsupervised Learning

Who Should Attend?

What are the Prerequisites?

Choose the Format That Fits Your Team

Get a Proposal Shaped to Your Needs

What Sets Edstellar Apart

Experienced Trainers

Proven Quality

Industry-Relevant Curriculum

Fully Customizable

Comprehensive Support

Global Multi-Location & Multilingual Training Delivery

Hear from Organizations We've Trained

Recognition That Motivates Your Team

We have Expert Trainers to Meet Your Introduction to Machine Learning Training Needs

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