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Kirjoita ensimmäinen arvio tuotteelle “Machine Learning in Data-Analytics”

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Machine Learning in Data-Analytics

16.-17.11.2022 – Hybrid implementation: Espoo / Distance training

Data Analytics and Machine Learning (ML) applications which are led by a data-driven approach to decision-making have helped world-renowned firms such as Netflix and Google double their commercial growth. ML is used in roughly 77 % of the gadgets we use today.

There are also lots of challenges associated with ML approach, such as poor quality of data, underfitting and overitting of training data, slow implementation and imperfections in algorithms with increase in data size. This course will introduce the learner to applied ML, focusing more on the feature engineering, techniques and implementations.


949 1299 

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Discount for groups bigger than 3 people. Choose your ticket based on how you want to attend.


Hintaan lisätään laskutuslisä 8 € ja ALV (24 %).


keskiviikko 16.11.

  • 8.45
  • Welcome! Registration and morning coffee
  • 8.55
  • Welcome distance learners! Signing in to the training
  • 9.00
  • Introduction to Data Analytics
  • Why and What is Data Analytics?
  • Need of Data Analytics
  • Challenges of conventional systems
  • 10.30
  • Break
  • 10.45
  • Working on Data Analytics
  • Data Analytics Life Cycle
  • Role and Responsibilities of Data Analytics
  • Data Analytics Applications
  • 12.00
  • Lunch break
  • 13.00
  • Exploratory Data Analysis and Exploration
  • Importing and Exporting data from an external source
  • Apply basic Functions on data
  • Data Exploration using bar graph, Histogram, Pie chart and Scatter plot
  • 14.15
  • Break
  • 14.30
  • Data Wrangling
  • Handling Missing Value
  • Reshaping Data
  • Data Normalization
  • 15.45
  • Conclusion of the day – End discussion
  • 16.00
  • The training day ends

torstai 17.11.

  • 8.45
  • Good morning!
  • 8.55
  • Distance learners registration starts
  • 9.00
  • Predictive Analytics I
  • Linear Regression and its use case
  • Multiple Linear Regression with its use case
  • Logistic Regression and Statistics Assessment
  • 10.30
  • Break
  • 10.45
  • Predictive Analytics II
  • Basics of Scikit-learn Library
  • Supervised and unsupervised learning
  • Use cases of learning Algorithms
  • 12.00
  • Lunch break
  • 13.00
  • Learning Algorithms-1
  • Decision Tree- Use case and Implementation
  • Random Forest-Use case and Implementation
  • Support Vector Machine – Use case and Implementation
  • 14.15
  • Break
  • 14.30
  • Learning Algorithms-2
  • Clustering – Use case and Implementation
  • Dimensionality reduction
  • Validation & evaluation of ML methods
  • 15.30
  • Conclusion of the day
  • 16.00
  • The training ends


Associate Professor at Software Engineering, LUT University

A.K.M Najmul Islam

He is an adjunct professor of Information Systems at Tampere University, Finland. He has received his PhD from the University of Turku, Finland, and M.Sc.  from Tampere University of Technology, Finland. He has published in other highly ranked journals such as IEEE.

an experienced machine learning pioneer, LUT University

Prabhat Kumar

Prabhat is currently working as a Post-Doctoral Researcher with the Department of Software Engineering, LUT School of Engineering Science, LUT University, Lappeenranta, Finland. He has many research contributions in the area of Machine Learning, Deep Learning, Federated Learning, Big Data Analytics, Cybersecurity, Blockchain, Cloud Computing, Internet of Things and Software Defined Networking. He has authored or coauthored over 20+ publications in high-ranked  SCI journals.

Analyse large data sets and make better decisions.

The participants will learn main ideas, fundamental concepts, and key algorithms in the fields of machine learning. The participants will use the most common machine learning algorithms to make sense of large amounts of data, which are applicable to most business and management problems.


This training will be helpful for the participants who want to learn implementation in more detail. This training will help participants to apply various ML techniques in their day-to-day business or class room projects by reading the trend of data.

Whom the training is suitable for?

Data, software, and IT professionals who want to obtain recent and cutting-edge viewpoint on data analytics and ML. You could also be an entrepreneur or consultant who wants to enhance  business growth and build expertise in data analytics and ML.

The participants are assumed to be familiar with basic python programming language. Knowledge on Pandas and Scikit-Learn package will be beneficial.

Improve your current job or find new jobs in data analytics and ML.

Gain knowledge regarding ethical and regulatory aspects when using ML.

Identify types of questions for which data analysis cannot provide accurate information.

Install, run, and apply machine learning tools to different kinds of data.

Prices of the training



Public sector: 899 €
Private sector: 1249 €
Valid until 16.9.2022 asti.


Get tickets


Public sector: 949 €
Private sector: 1299 €
Valid until 14.10.2022 asti.


Get tickets


Public sector: 999 €
Private sector: 1349 €
Valid until  16.11.2022 asti.


Get tickets
Group offer

Automatic discount for groups bigger than 3 people. You can also email us at

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