Predictive Analytics 101

Data science and Predictive Analytics

The goal of data science is to extract knowledge and insights from large amounts of structured and unstructured data. Today in scientific research or business firms, data science plays an important role in gaining insight into complex systems.
Data science is an interdisciplinary area with a growing job market in science, economy, business, and engineering.

The goal of this course is to introduce students to data science theory and practice. key techniques and tools used in Big Data analytics.

What will you achieve after this course?

We show the steps of a data science project, from problem definition to
implementation in a practical code-based approach. Major methods for data preparation and feature engineering are presented. Then, important statistical and machine learning approaches for model building are discussed and implemented in R and Python. Tools for model validation and model interpretations are reviewed. Then, the implementation and deployment of data science models in cloud environments are

This course has live sessions of 2 hours for 10 weeks. You will be engaged by assignments, projects, and direct feedback from the instructor.

This course is designed to assist students who are interested to use data science in their academic endeavor, and those who are looking to enrich their analytic skills and seek a data science job.

You can take part in the first two sessions for free.

The unique Features of this course:

✔ 20 Hours of Live Instructor-Led Training
✔ Learn By Doing Projects
✔ Industry experienced Instructor from IBM
✔ ComeMit Certificate
✔ Multi language Training and Support

Made with ❤️ in Germany

What you will learn:

Data Science and Predictive Analytics

Basic familiarity with R or python
Basic understanding of statistical concepts

You will learn:

– Introduction to Data Science
– Extract, Transform, Load (ETL)
– Exploratory Data Analysis
– Feature Engineering
– Linear models, Generalized Linear Models (GLM)
– Decision Trees, Random Forests, Gradient Boosting
– Artificial Neural Networks, Deep Learning
– Introduction to Clouds, Model Deployments

Download the detailed course syllabus

You can fill-up your resume with professional use cases
You can start new career in Data science

And Yes!
✔✔ You will become a Data Scientist!

Mo Gorji

Mo Gorji

Senior Data Scientist at IBM Data Science & AI Elite (DSE)

Mo Gorji has received his PhD in electrical engineering from North Carolina A&T State University. He has worked as postdoc researcher in University of Arizona. In 2019, he has joined IBM and currently working as a senior data scientist in IBM Data Science & AI Elite (DSE) team. 

Dr. Gorji has published about 30 papers in electrical engineering and data science domain, and has been a reviewer for several conferences and journals. He worked as a researcher in multiple data science projects in academia funded by NSF, DoT, and DARPA. He has also accomplished several business data science projects in marketing, retail, insurance, supply chain and finance domains.

Weekly Course


✔20 hours of Live Instructor-Led Training
(Weekly 1 session, 2 hours)

✔20 Hours of Assignments and Reviews by Professionals

✔20 Hours of Continual Learning Support

Start from Friday 05.11.2021
16-18 pm (CET)

Enrolment is free

After the first two sessions you will pay 449 €