Practical teaching
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ARTIFICIAL INTELLIGENCE · ADVANCED LEVEL
Data Science & Machine Learning
Explore essential concepts of data science, including data processing, statistical analysis, and visualization. Learn supervised and unsupervised machine learning algorithms and apply them using Python and relevant libraries. This course equips students for roles in data-driven decision making. Our expert instructors bring years of experience, ensuring training is enriched with practical labs and real-world examples.
Advanced20 weeks80 hoursOn-site
Your selected course will be carried into Ingress Portal.
COURSE HIGHLIGHTS
Mentors
The knowledge and skills you learn at the academy will be further strengthened with the mentor syste
Academic transcript
Assignments and projects are checked by the instructor, and your knowledge and skills are determined
CONDENSED SYLLABUS
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01Introduction to Python11 lessons+
Introduction to Programming
Conditional Statements
Strings
Loops
Functions
Data Structures & Algorithms (for Data Science)
Comparative Analysis of Data Structures
Pandas for Data Analysis/Data Cleaning/Data Processing
NumPy
Data Visualization: Plotly, Matplotlib, Seaborn
OOP
02Statistics in Python7 lessons+
Sample & Population differences, Mean, Median, Mode, Variance, Deviation
Philosophy of Randomness, Random Variables
Covariance and Correlation
Quantiles, Outlier Detection and Exclusion
The Application and Moral of Standardization and Normalization of the Data
Distributions: Normal Distribution, Binomial Distribution
P value, Hypothesis testing
03Machine Learning19 lessons+
Supervised vs Unsupervised Learning
Machine Learning Model Preparation Stages
Regression Analysis: Linear Regression
Gradient Descent in Linear Regression
Logistic Regression
Regularization
Variance vs Bias
Error Metrics
K-Means
Decision Tree
PCA
Anomaly Detection
Recommender System
Neural Networks
Large Scale Machine Learning
Convolutional Neural Networks
Recurrent Neural Networks
Timeseries Analysis
Data Cleaning and Preprocessing Procedures in Natural Language Processing / Understanding / Generation
UPCOMING GROUPS
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STARTS
27 January 2026
On-site- Schedule
- To be announced
- Format
- On-site
- Duration
- 20 weeks · 80 hours
- Language
- Confirm with advisor
YOUR INSTRUCTOR TEAM
Specialists matched to the modules they teach.
Course delivery is supported by practitioners across engineering, architecture and production backend development.
Natig Mamishov
Data ScientistYelo Bank“The program helped me connect individual skills into the way real teams design, build and deliver software.”
See real graduate stories from the Ingress community.
Explore graduate resultsAPPLICATION THROUGH INGRESS PORTAL
Your course stays selected while you create your account.
We use one Portal account for applications, assessments and future learning progress. You will not need to email your details or select the training again.
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Create or sign in to your Portal accountYour contact details stay connected to one student profile.
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Confirm your application detailsData Science & Machine Learning is preselected.
- 03
Submit your applicationThe admissions team receives it immediately and can follow up from the Portal.
SELECTED TRAININGData Science & Machine LearningOn-site
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