Course Data Science with KNIME | DATA SCIENCE duration Online
The KNIME Analytics platform has been called the "killer app" of machine learning.
No programming skills are required. Both those who want to work in the field of Data Science, Data Engineering, Data Analysis and Business analysis, and those who already work in the social media field and wish to grow and pursue a career as a Social media analyst, can access this specialization module.
Data Analytics with Knime - basic level | 16 hours
KNIME Analytics is the most powerful and complete free platform for drag-and-drop analysis, machine learning, statistics and ETL (Extract, Transform, Load). The latter is the data collection process that refers to the three steps (extraction, transformation, loading) used to organize and centralize data from multiple sources in a single repository. It is often used to create a data warehouse.
Ultimately, KNIME offers the possibility to create data processing flows independently and very quickly (Technology Agnostic). It also allows users to perform additional operations on remote data sources (both relational and non-relational) and with different types (from csv, json to mysql and elastic). Finally, it also implies the use of artificial intelligence and e Machine learning for both ordinary work and R&D.
Data Science with Knime - advanced level | 16 hours
This module, which does not require programming knowledge, implies the development of data processing pipelines for the analysis, updating and ad-hoc operations in a relatively short time.
After this course participants can easily do cleaning of noisy or dirty data and missing values. filtering, data integration with concatenation and joins. and do all kind of data transformations such as discretization, normalization, or pivoting.
1. Intro to Knime, Environment 2. Working with files. (Excel, CSV, Text) 3. Data Manipulation (Table, Row & Column level) 4. Join / Cross Join / Group by / Pivot / Unpivot 5. Variables 6. Python in Knime 7. Mini project 1
This Advanced Module also includes Artificial Intelligence and Machine Learning applications and methods.
1. Time Processing 2. Relational Database OPS (read, write, update + Quick SQL Queries Review) 3. Error handling 4. Reusability with Meta-Nodes & Components 5. Advanced & AD-HOC Nodes 6. Mini project 2
1. Text Processing 2. AI & ML in Knime a. Bayes b. Clustering c. Rule Induction d. Neural Network e. Decision Tree, Decision Tree Ensemble f. Misc. Classifiers g. Linear / polynomial Regression 3. Project 2
No programming skills are required. Both those who want to work in the field of Data Science, Data Engineering, Data Analysis and business analysis, and those who work in the social media field and want to pursue a career as a Social media analyst can access this specialization module.
Personal notebook for practical exercises.
64-bit dual core CPU on x86-64
Operating System: Linux / Mac Os X / Windows