Data Science for Professionals Course

DATA SCIENCE
& ML Course

We are not just implement new technology for the sake of innovation, but our team is focused to offer solutions to change the company culture and increase operational efficiency by using training methodologies to enforce data driven culture and transfer tested know how for modern business collaboration tools and techniques.

Data Scientist Training for the data-driven decision processes. 

Our course is focused integrating new technologies—big data, cloud computing, artificial intelligence, machine learning, to drive supplementary profit in every area of the business.

Built a data science career

Data Science and Machine Learning

You will be able to upgrade your data analytics skills by learning the theory and practical application.

01

Business knowlege

Our Digital Transformation course provides an overview of business opportunities and impact in digital transformation from data to process automation.

02

Data Analysis

2nd course part focuses on topics useful to any team: Distribution Analysis, Correlation Analysis, Multivariate Analysis, and Time Series Analysis.

03

AI/ML Applied

3rd part focuses on AI and ML. This part include producing the best quality data for use in crafting valuable machine learning models: data profiling, wrangling string data, and engineering date-time features.

Benefits

The average salary for Data Scientists in these industries ranges up to $110,000 to $117,000 per year

Practical, Hands-on Training

The growing need for data science experts, due to the vast amounts of data generated by digital technologies.

why

Upgrade your career path towards a Fast Expanding and High-in-Demand Field at Every Level.

 

Contact Us⟶

Upgrade your career

Course curriculum

  • Digital Transformation
  • Data structures
  • Business metrics
  • Data culture
  • Process analysis
  • Process automation
  • Case studies 
  • Career path
  • Descriptive statistics
  • Probability theory
  • Statistical inference
  • Hypothesis testing
  • Regression analysis
  • Time series analysis
  • Experimental design
  • Model validation
  • Introduction to big data
  • Hadoop ecosystem
  • MapReduce programming
  • Spark fundamentals
  • Distributed computing
  • NoSQL databases
  • Real-time data processing
  • Streaming analytics
  • Python basics
  • Data structures in Python
  • Control flow statements
  • Functions and modules
  • File handling in Python
  • Object-oriented programming
  • Exception handling
  • Python libraries for data science
  • Data science overview
  • Data lifecycle
  • Intro to Python programming
  • Data visualization
  • Exploratory data analysis
  • Data ethics
  • Project management
  • Case studies
  • Supervised learning
  • Unsupervised learning
  • Model evaluation metrics
  • Feature engineering
  • Model selection techniques
  • Ensemble learning
  • Dimensionality reduction
  • Hyperparameter tuning
  • Deep learning basics
  • Neural networks
  • Convolutional neural networks (CNNs)
  • Recurrent neural networks (RNNs)
  • Natural language processing (NLP)
  • Image processing
  • Transfer learning
  • Reinforcement learning
  • Predictive analytics
  • Prescriptive analytics
  • Recommender systems
  • Fraud detection
  • Customer segmentation
  • Sentiment analysis
  • Healthcare analytics
  • Social media analytics

Join course

VT Risk offers a data science course designed to equip you with the skills and knowledge needed to excel in this field.