Corporate Machine Learning With Python Training Course

Name: Machine Learning with Python Training
Availability: InStock

Edstellar's instructor-led Machine Learning with Python Training Program equips your organizations with practical skills and techniques to leverage data-driven insights. Enhance your team's proficiency in Python programming, unleash machine learning algorithms' capabilities, and gain a competitive edge in today's data-centric world.

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 Machine Learning With Python Corporate Training

Machine Learning with Python refers to using Python to apply machine learning techniques for analyzing data, making predictions, and automating decision-making processes. Machine Learning with Python is immensely beneficial for organizations, offering a pathway to transform vast amounts of data into actionable insights, thereby enhancing decision-making processes. This training explores the concept of machine learning through Python by showcasing how its rich ecosystem of libraries and tools can be utilized to develop sophisticated models that predict, classify, and analyze data in ways that can significantly enhance decision-making and operational efficiency within organizations.

Edstellar instructor-led Machine Learning with Python course distinguishes itself with its flexibility in offering virtual/onsite training options, catering to organizations' varied logistical needs and preferences. This adaptability ensures that teams have access to high-quality learning resources and expert instruction regardless of geographical location. Moreover, the Edstellar training program stands out for its emphasis on customization, allowing the course content to be tailored to meet each organization's specific challenges and goals. Professionals will benefit from practical, hands-on experience, working on real-life projects and scenarios that reinforce learning outcomes and equip them with actionable skills.

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.

Predictive Modeling
Predictive Modeling is the process of using statistical techniques to forecast future outcomes based on historical data. This skill is important for data analysts, marketers, and financial analysts, as it enables informed decision-making and strategic planning.
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.
Data Visualization
Data Visualization is the ability to represent data graphically, making complex information accessible and understandable. this skill is important for analysts and decision-makers to identify trends, insights, and patterns effectively.
Data Processing Automation
Data Processing Automation involves using technology to streamline and automate data handling tasks. This skill is important for roles in data analysis, IT, and operations, enhancing efficiency and accuracy.
Custom Algorithm Development
Custom Algorithm Development involves creating tailored algorithms to solve specific problems. this skill is important for data scientists and software engineers to optimize solutions and enhance performance.
Model Optimization
Model Optimization is the process of refining machine learning models to enhance performance and efficiency. This skill is important for data scientists and AI engineers, as it ensures accurate predictions and resource-efficient solutions.

What Your Team Will Achieve After This Training

Design and implement predictive models to forecast market trends, customer behavior, and operational efficiencies, leveraging Python's powerful libraries like Scikit-learn, Pandas, and NumPy
Apply statistical analysis and data visualization techniques to make informed decisions based on data, using Python tools such as Matplotlib and Seaborn for insightful visual representations
Automate data processing tasks, including cleaning, normalization, and feature engineering to prepare datasets for analysis, enhancing the accuracy and effectiveness of machine learning models
Develop custom machine learning algorithms for classification, regression, clustering, and recommendation systems tailored to specific business needs and objectives
Optimize machine learning models with hyperparameter tuning and cross-validation techniques to achieve the best possible performance, ensuring reliable predictions and outcomes
Deploy machine learning models into production environments, integrating them with existing systems to improve decision-making processes and operational workflows

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.

Python for Machine Learning

Getting started with Python
- Installing Python and setting up the environment
- Understanding Python syntax and basic commands
Libraries for machine learning
- Introduction to NumPy and pandas
- Exploring Matplotlib and Seaborn for data visualization
- Utilizing Scikit-learn for machine learning
Writing your first Python program
- Basic programming concepts
- Working with data structures
Best practices in Python programming
- Code organization and readability
- Debugging and error handling

Basic Statistics for Machine Learning

Understanding data types and measures
- Numerical vs categorical data
- Central tendency and variability
Probability basics
- Probability theory and rules
- Distributions and their significance
Hypothesis testing and confidence intervals
- Conducting hypothesis tests
- Interpreting confidence intervals
Correlation and regression analysis
- Exploring relationships between variables
- Fitting a linear regression model

Introduction to Machine Learning

Machine learning fundamentals
- Definition and types of machine learning
- Applications of machine learning
The machine learning workflow
- Data collection to model deployment
- Evaluating model performance
Overfitting and underfitting
- Diagnosing model performance issues
- Strategies for model improvement
Choosing the right algorithm
- Algorithm selection criteria
- Overview of common machine learning algorithms

Data Processing for Machine Learning

Data cleaning and preparation
- Handling missing values
- Dealing with outliers
Feature engineering
- Creating new features
- Feature scaling and normalization
Data splitting
- Training and test set creation
- Cross-validation techniques
Dimensionality reduction
- Principal component analysis (PCA)
- Feature selection methods

Machine Learning Algorithms

Supervised learning algorithms
- Linear and logistic regression
- Decision trees and random forests
Unsupervised learning algorithms
- K-means clustering
- Hierarchical clustering
Neural networks and deep learning
- Basics of neural networks
- Introduction to deep learning frameworks
Ensemble methods and model evaluation
- Boosting and bagging techniques
- Metrics for model evaluation

Building and Training Machine Learning Models

Data preprocessing for model building
- Feature extraction and selection
- Preparing data for training
Model training and validation
- Training models with Scikit-learn
- Validating model accuracy
Hyperparameter tuning
- Grid search and random search
- Using cross-validation for tuning
Model deployment and monitoring
- Deploying models to production
- Monitoring and updating models

Property Estimation with ML

Introduction to property estimation
- Significance in various fields
- Overview of ML applications
Data sources and feature selection
- Identifying relevant data
- Selecting features for property estimation
Building models for property estimation
- Choosing the right algorithm
- Training and testing models
Case studies and applications
- Real-world examples of property estimation
- Lessons learned from case studies

Who Should Attend?

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

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

What are the Prerequisites?

Professionals should have a basic understanding of Python programming, algebra, calculus, statistics, probability, and introductory data analysis techniques using Python libraries like Pandas and NumPy to take the Machine Learning with Python training course.

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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 Machine Learning with Python 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 Machine Learning with Python 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 Machine Learning with Python 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

"The Machine Learning with Python course revolutionized how I approach my daily responsibilities. As a Principal Cloud Engineer, understanding industry best practices was essential, and this training provided invaluable real-world experience. I've confidently led multiple high-visibility initiatives leveraging this comprehensive knowledge. The instructor's insights on interactive labs have proven instrumental in my professional advancement.”

Ezekiel Chandler

Principal Cloud Engineer,

Cognitive Computing Solutions Provider

"The Machine Learning with Python training enhanced my ability to architect and implement sophisticated technical mastery strategies. Understanding advanced methodologies through intensive hands-on exercises exercises proved invaluable for client This expertise enabled us to secure a transformative contract with a Fortune 100 organization. The detailed exploration of real-world case studies provided methodologies I leverage in every engagement.”

Ma Qiang

Principal Frontend Developer,

Predictive Analytics Firm

"The Machine Learning with Python training gave our team advanced strategic frameworks expertise that revolutionized our operational excellence approach. As a Senior Full Stack Developer, understanding expert-led workshops and across our entire portfolio. Our team delivered record-breaking results in the subsequent quarter, exceeding all targets. This training has become foundational to our team's strategic capabilities and continued growth.”

Hisham Bassam

Senior Full Stack Developer,

AI Solutions Platform Provider

“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 Machine Learning With Python 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.

Priyadharshini

Chennai, India

Trainer since

August 1, 2022

Corporate Machine Learning With Python Training Course

Drive Team Excellence with Machine Learning With Python Corporate Training

Skills Your Employees Will Gain

What Your Team Will Achieve After This Training

Topics & Program Outline

Python for Machine Learning

Basic Statistics for Machine Learning

Introduction to Machine Learning

Data Processing for Machine Learning

Machine Learning Algorithms

Building and Training Machine Learning Models

Property Estimation with ML

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 Machine Learning With Python Training Needs

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