Building Intelligent Applications with AI and ML - Level 1 Training in Finland

  • Delivery Method: Online Instructor-Led / Classroom Based / Onsite
  • Participation Model: Public Training / Private / In-House Training
  • Duration: 3 Days
  • Price: From €2,900 +TAX
  • Upcoming Date:
  • UK & Finland Based Global Training Provider
Exclusive - Learn the fundamentals of Artificial Intelligence and Machine Learning to develop intelligent applications.

Intelligent applications that are developed using Artificial Intelligence and Machine Learning are helping businesses take critical initiatives. These applications incorporate the power of predictive and prescriptive analytics, consumer data, and cutting-edge technologies. They are used by many organizations and enterprises to automatically discover, learn and give predictions and recommendations. Examples of such applications include risk analysis, fraud detection, and prevention, personalized health services, etc.

This course focuses on covering the fundamentals like Statistics, probability, and a variety of machine learning algorithms that form the building blocks for the development of intelligent applications.



Is This The Right Course?

  • Basic familiarity with Python programming.
  • Basic understanding of Data Terminologies.
  • Familiarity with enterprise IT.
  • Foundational knowledge in mathematical concepts like linear algebra and probability.
  • Basic linux skills.
  • Basic SQL skills.

Who Should Attend?

This is an introduction-level hands-on course suitable for everyone who wants to explore the field of Artificial Intelligence (AI) and Machine Learning (ML). This course covers the foundations of AI, ML, programming, search, and logic along with their applications to computational problems. This is a level 1 course in building your skills for developing Intelligent applications using Machine Learning and Artificial Intelligence. Anyone who wants to shift their career to AI and ML can attend this course such as

  • Business Analysts
  • Data Analysts
  • Developers
  • Administrators
  • Architects
  • Managers
  • Anyone new to AI and ML who wants to understand the foundations of ML and AI for developing ML applications.

We can organize this training at your preferred date and location.
HAVELSAN
ASELSAN
PepsiCo Türkiye
JTI TÜTÜN ÜRÜNLERİ SANAYİ A.Ş.
ING Bank
DHL
MASTERCARD
Huawei
TotalEnergies
Mercedes-Benz Türk A.Ş.
Goodyear
FORD OTOMOTIV SANAYI A.S.
3M COMPANY
Schneider Electric
Central Bank of Azerbaijan
BP Petrolleri
Procter & Gamble (P&G)
Qatar Foundation
Bank Of China
GlaxoSmithKline (GSK)
MORGAN STANLEY & CO Inc
Novo Nordisk
DEUTSCHE BANK
Azerbaycan Cumhuriyeti Emek ve Ahalinin Sosyal Güvenliği Bakanlığı
ACCENTURE

Prerequisites

  • Basic familiarity with Python programming.
  • Basic understanding of Data Terminologies.
  • Familiarity with enterprise IT.
  • Foundational knowledge in mathematical concepts like linear algebra and probability.
  • Basic linux skills.
  • Basic SQL skills.

What You Will Learn

  • Explore Jupiter notebooks and Python
  • Recall and Remember Statistics and Probability concepts and explore coding in Python for data analysis
  • Understand advanced probability concepts and data visualizations using libraries such as Matplotlib, seaborn
  • Understand various Machine Learning Algorithms and their applications
  • Understand various Predictive Models
  • Apply Machine Learning algorithms to build predictive models
  • Understand Recommendation Systems
  • Understand how to deal with data in the real world
  • Apply Machine Learning on Big Data using Apache Spark
  • build UI and REST APIs for ML models

Training Outline

  1. Getting Started with Jupitor Notebooks and Python
    • Installing Python 3.x and Data Science environment
    • Importing required modules
    • Writing and executing Python code in Jupiter notebook
    • Understanding Data Visualizations using Matplotlib and seaborn.
    • Running Python scripts
    • Statistics and Probability Essentials
      • Understanding Descriptive and Inferential Statistics and the difference between them
      • Understanding Data types - quantitative and qualitative
      • How to understand the spread of data with measures of Central Tendency and dispersion
      • Understanding dirty data - missing values and outliers
      • Understanding probability distributions, Probability density function and probability mass function
      • Understanding the spread and distribution of data using Python.
      • Introduction to Percentiles and Moments and why they are important?
      • Understanding Hypothesis Testing and various types of Hypothesis tests with their applications.
    • Advanced Probability Concepts
      • Covariance and Correlation and their role in understanding Data
      • How Conditional Probability helps in predictive analytics?
      • Baye's Theorem and it's applications
  2. Machine Learning Algorithms
    • Understanding Different Types of Machine Learning Algorithms - Supervised, Semi-Supervised, UnSupervised, Reinforcement Learning
    • Distinguish between Linear and Non-Linear, Distance-based, Parametric and Non-Parametric machine learning models
    • Understanding different phases of building Machine Learning Models
    • Differentiate between Classification and Regression
    • An overview of linear and logistic regressions
    • An overview of decision trees and random forests
    • An overview of KNN and SVM
    • How to Build Predictive Models with available data?
      • Understanding your data - Data loading and descriptive analysis
      • Dealing with unclean data - Data Cleaning and Pre-processing
      • Building machine learning models with Linear Regression and Logistic Regression
      • Understand when to apply Polynomial Regression and build a model
      • Building a predictive model using multivariate regression
      • Multi-level models
  3. Evaluating and Tuning your models with advanced Machine Learning with Python
    • Understanding model fit - overfitting and underfitting, Bias-Variance Trade-Off
    • Understanding model evaluation metrics for regression and classification
    • Understanding K-fold cross-validation to avoid overfitting
    • Bayesian models
    • Implementing Email spam classifier with Naïve Bayes Classifier
    • Understand K-Nearest Neighbors Algorithm and using KNN for predictive analytics
    • Understand Gradient Descent, Stochastic Gradient Descent, and tune your model
    • Understand ensemble methods, bagging and boosting
    • Understand various boosting algorithms
    • Unsupervised Machine Learning
      • Understanding Clustering
      • Understand K-Means Clustering with a case study
      • Understanding Dimensionality Reduction and Principal Component Analysis
      • Applying PCA on a real world dataset
    • Understanding and Building Recommendation Systems
      • What are recommendation Systems
      • Understanding User-based and Item-based Collaborative Filtering
      • Finding similar movies
      • Improving the results of movie similarities
      • Making movie recommendations to people
      • Improving our recommendation results

Why Choose Us

Experience Building Intelligent Applications with AI and ML - Level 1 in Finland through Bilginç IT Academy's live and interactive virtual classroom environment. Join a Public course as an individual delegate or arrange a dedicated Private / In-house online training program exclusively for your organization.

  • Delivery Method: Online Instructor-Led
  • Participation Model: Public / Private (In-house)
  • Live and Interactive Training: Connect with your instructor in real time and actively participate through discussions, Q&A sessions, practical exercises, and group activities.
  • Flexible Participation: Join the training from your home, office, or any location with a suitable internet connection.
  • Expert Trainer Network: Learn from experienced trainers with strong industry backgrounds and practical field expertise.
  • Over 30 Years of Training Expertise: Benefit from Bilginç IT Academy's professional training experience since 1995.
  • Worldwide Access: Join our live virtual classrooms from Finland or anywhere else in the world, or arrange a dedicated online training program for your organization.

Experience Building Intelligent Applications with AI and ML - Level 1 through face-to-face Classroom Based training in Finland. Training can be delivered as a Public course open to individual delegates or as a dedicated Private / In-house class for your organization.

  • Delivery Method: Classroom Based
  • Participation Model: Public / Private (In-house)
  • Face-to-Face Learning: Interact directly with your instructor and fellow delegates in an engaging classroom environment.
  • Experienced Trainers: Learn from specialists with extensive industry experience and practical real-world knowledge.
  • Professional Training Environment: Attend training in comfortable, well-equipped classrooms designed to support effective learning.
  • Practical Learning: Depending on the course, reinforce your knowledge through hands-on exercises, scenarios, case studies, and instructor-led activities.

Arrange Building Intelligent Applications with AI and ML - Level 1 in Finland as a dedicated Onsite training program for your organization. Bilginç IT Academy trainers can deliver the training at your office or another location of your choice, with the program planned around your team's requirements and business objectives.

  • Delivery Method: Onsite
  • Participation Model: Private (In-house)
  • Training at Your Preferred Location: Organize the training at your company's office or another location selected by your organization.
  • Tailored Course Content: Adapt the training program to your projects, team structure, existing skill levels, and specific business requirements.
  • Team-Focused Learning: Develop your team around a shared knowledge base while strengthening internal collaboration and knowledge transfer.
  • Flexible Scheduling: Plan the training dates, location, and program according to your organization's operational requirements.
  • Worldwide Onsite Delivery: Arrange the training in Finland or at another preferred location worldwide. Bilginç IT Academy trainers can travel to your selected location to deliver the dedicated training program.
Contact us for more detail about our trainings and for all other enquiries!

Building Intelligent Applications with AI and ML - Level 1 Training Course in Finland Schedule

Join our public courses in our Finland facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

We can organize this training at your preferred date and location.
09 lokakuuta 2026 (3 Days)
Helsinki, Espoo, Tampere
€2,900 +TAX
11 lokakuuta 2026 (3 Days)
Helsinki, Espoo, Tampere
€2,900 +TAX
13 lokakuuta 2026 (3 Days)
Helsinki, Espoo, Tampere
€2,900 +TAX
18 lokakuuta 2026 (3 Days)
Helsinki, Espoo, Tampere
€2,900 +TAX
21 lokakuuta 2026 (3 Days)
Helsinki, Espoo, Tampere
€2,900 +TAX
03 marraskuuta 2026 (3 Days)
Helsinki, Espoo, Tampere
€2,900 +TAX
12 marraskuuta 2026 (3 Days)
Helsinki, Espoo, Tampere
€2,900 +TAX
13 marraskuuta 2026 (3 Days)
Helsinki, Espoo, Tampere
€2,900 +TAX

Finland is globally recognized as a leader in education and high-tech innovation, particularly in the fields of mobile telecommunications and software engineering. Helsinki, Espoo, and Tampere form a powerful tech triangle, supported by the research excellence of Aalto University and a long history of pioneering technology. The Finnish tech culture is built on a foundation of early digital adoption, making it a world leader in IoT, cybersecurity, and gaming technology. Our IT training programs in Finland are designed for a workforce that demands the highest technical standards and precision. We focus on delivering advanced certifications in Network Security, Software Architecture, and Cloud Native development, ensuring that Finland continues to set the benchmark for technological sophistication in the Nordic region.

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