Junior Data Scientist Training Modules
This 3-month program provides beginner-to-intermediate level knowledge and practical skills in data science, equipping participants with a foundational preparation to analyze real data, build models, and interpret results. Learners will gain hands-on experience with the end-to-end data science process — from data cleaning and analysis, to developing and evaluating machine learning models, to applying them in business decision-making — through practical case studies.
Program Structure (3 Months)
Month 1: Foundations
- Module 1. Data Science Fundamentals
- Module 2. Python for Data Analysis
- Module 3. Statistics & Probability
Month 2: Data Analysis & Machine Learning
- Module 4. Data Cleaning & Exploration
- Module 5. Machine Learning Fundamentals
- Module 6. Feature Engineering & Model Evaluation
Month 3: Applied Data Science
- Module 7. Advanced Machine Learning
- Module 8. Model Deployment Fundamentals
- Module 9. Data Visualization & Storytelling
- Mini Project. Capstone Project
Start Date: Tuesday, May 19 Class Days: Tuesday, Thursday Schedule: 18:00–20:30 Location: Zaisan, Sky Wing Office, 6th Floor, Room 601
Junior Data Scientist Training
Junior Data Scientist-ийн сургалтын төлбөр нийт 4,800,000₮ ба суудал баталгаажуулахад 20% буюу 960,000₮-ийг төлнө.
Learning Outcomes
Upon completing the program, graduates will have acquired the following skills:
✔ Collecting data from multiple sources, cleaning it, and preparing it for analysis
✔ Conducting exploratory data analysis (EDA) to uncover data characteristics and relationships
✔ Performing data analysis and transformation using Python
✔ Processing data using NumPy and Pandas
✔ Applying fundamental statistical concepts to real-world data
✔ Conducting hypothesis testing and basic statistical analysis
✔ Understanding core machine learning algorithms
✔ Building and testing regression, classification, and clustering models
✔ Performing feature engineering
✔ Carrying out model training, validation, and evaluation
✔ Measuring model performance (accuracy, precision, recall, etc.)
✔ Understanding overfitting/underfitting and improving models
✔ Using data visualization to interpret results and tell data-driven stories
✔ Analyzing business cases using data science methodologies
✔ Conducting reproducible analysis in a notebook environment
✔ Completing a mini project on a real-world case
Graduates will be fully prepared at the Junior Data Scientist level, capable of analyzing real data, building foundational machine learning models, and interpreting results for business decision-making.
Successful graduates will receive an official certificate validating their knowledge and skills, and will be recommended to major domestic organizations.
Who is a Data Scientist?
A Data Scientist is a professional who extracts meaning, trends, and predictions from data, helping organizations make data-driven decisions and develop data-informed products. They use statistics, programming, and machine learning (ML) to build models that forecast the future, understand behavior, and solve business problems.
Demand Trends
Demand for data scientists remains very high, with job openings projected to grow by 34–36% between 2024 and 2034 — a significantly faster rate than the average across all occupations. As every industry faces the need for data-driven decision-making, approximately 23,400 new positions are expected to be created each year.
Rapid growth: According to BLS projections, data scientist roles will grow by 34% between 2024 and 2034, adding approximately 82,500 new positions in total.
Cross-industry expansion: Demand is not limited to the tech sector — as retail, healthcare, finance, logistics, and other industries undergo digital transformation, the need for data scientists continues to grow.
Demand for experienced professionals: While entry-level positions exist, there is even greater demand for experienced practitioners. Approximately 69% of job openings require advanced specialization in areas such as AI and machine learning.
Salary: International average of $155,957
Factors Driving Demand
Explosive growth in data volume: As the amount of data increases, there is a critical need for analytical professionals who can extract business value from it.
Rise of AI: As generative AI and other AI solutions are adopted, demand grows for professionals who can develop, utilize, and manage these technologies.
Data-driven decision-making: Organizations are increasingly relying on analytics and data analysis to optimize operations and develop new products and services.
Data science remains one of the highest-paying and most future-proof careers available today.
