Data Science Training in Astana, Kazakhstan

Data Science training equips participants with the skills to analyze, interpret, and derive insights from complex datasets using statistical and computational methods. The course covers essential topics such as data cleaning, exploratory data analysis, machine learning, and data visualization using tools like Python, R, and SQL. Participants learn to work with real-world datasets, build predictive models, and communicate insights effectively through visualizations and reports. Hands-on exercises focus on practical applications, such as building classification models, optimizing algorithms, and deploying data-driven solutions. By the end of the training, attendees will be able to apply data science techniques to solve business problems, make data-driven decisions, and add value to their organizations.

Foundations of Data Science

1. Introduction to Data Science
• What is Data Science?
• Applications in various industries
2. Understanding Data
• Types of data: structured and unstructured
• Basics of data collection and storage
3. Python Basics for Data Science
• Setting up Python for data science
• Introduction to key libraries: NumPy, Pandas
4. Data Manipulation with Pandas
• Cleaning and transforming data
• Operations like filtering, grouping, and sorting
5. Practical Exercise

Visualization and Machine Learning Basics

1. Data Visualization
• Using Matplotlib and Seaborn
• Creating plots like histograms, scatter plots, and bar charts
2. Exploratory Data Analysis (EDA)
• Identifying trends and patterns in datasets
3. Introduction to Machine Learning
• Overview of supervised and unsupervised learning
• Building a simple prediction model using Scikit-learn
4. Hands-On Exercises: Analyzing and visualizing a real-world datasets