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The "Data Analyst + AI" course at GortsUp Academy in Yerevan is designed for beginners. Duration: 6 months. Classes are held in Yerevan at 4 Tigran Mets and on an online platform (hybrid format). Price: from 49 200 ֏ per month with a 12-month installment plan. From the 3rd month of study, a job placement support program is available, and 79% of students find a job during their studies. The academy has been on the market since 2022, with 2500+ graduates.
Programming with neural networks
We learn AI tools and how to apply them in data analysis.
Job placement support program
From the 3rd month of study
Small groups with active involvement of everyone
Up to 22 students per group
Hands-on learning comes first
More than 50% of the course is practical work
Partner
Partner
Partner
Partner
No. 1 in Armenia with a job placement program
Aravoty Shantum / GortsUp Academy
Shant TV
Aravoty Shantum / GortsUp Academy
Shant TV
Recruit Days 2024
Armenia Today
Recruit Days 2024
Hayk media
- 2500+Graduates
- Since 2022On the market
- 9,2Client trust index
- 79%of graduates get jobs
Our students about us
The lesson was very interesting, everything was accessible, and the explanations were interesting and clear.
It was a very productive lesson.
Interesting and engaging.
I'm satisfied.
Very engaging and interesting.
It was a very productive lesson.
Interesting and engaging.
I'm satisfied.
Very engaging and interesting.
Very good, the lecturer explained everything clearly.
The lesson was ideal, very good, we discussed everything as a group and all of us were involved.
I was involved, we asked the lecturer questions, it was an interactive lesson
We talked about professional topics, the lesson was interesting. The lecturer explained in an accessible way
The lesson was ideal, very good, we discussed everything as a group and all of us were involved.
I was involved, we asked the lecturer questions, it was an interactive lesson
We talked about professional topics, the lesson was interesting. The lecturer explained in an accessible way
A very good, positive, knowledgeable and smart person, the lecturer. I'm very happy with your academy. I have a very good opinion of you, and the lecturer was very professional.
Very interesting, I was very well engaged.
A quite pleasant lesson, I'm satisfied.
The lesson was very interesting, the lecturer is a good specialist, I was engaged in the lesson.
Very interesting, I was very well engaged.
A quite pleasant lesson, I'm satisfied.
The lesson was very interesting, the lecturer is a good specialist, I was engaged in the lesson.
The lesson was interesting, I was engaged, and the lecturer was equally attentive to everyone.
The information about the profession was interesting.
The lecturer explains everything very well.
Very good, I have positive emotions from the lesson.
The lesson went by in an interesting way, the lecturer is a pleasant person.
The information about the profession was interesting.
The lecturer explains everything very well.
Very good, I have positive emotions from the lesson.
The lesson went by in an interesting way, the lecturer is a pleasant person.
About the profession
A Data Analyst + AI is a specialist who analyzes data using AI tools.
Data analysis with AI
With interest
AI to speed up workflows
Practical
Data visualization and reports
Professional
Task automation with AI
Confident
DevOps: the choice for 2030
By 2030 the world will be short of 4 500 000+ specialists in this profession with AI knowledge.
- You love dataEverything must work reliably, automatically and without errors.
- You love automationYou prefer writing scripts and automating processes instead of doing manual work.
- You are interested in technologyYou want to work with Docker, Kubernetes, Linux, Cloud and modern AI tools.
- You think like an engineerYou love analyzing, solving complex problems and building reliable systems.
When it is time to change your profession
If you ask yourself these questions, it is time to try something new
-
You earn as much as you want, not as much as happens to come. -
You see your acquaintances changing jobs and their standard of living, while nothing changes for you. -
A year from now it will be harder for you to reach senior positions than it is today. -
You keep putting off a change of profession because you are afraid of making a mistake again. -
Will your skills become outdated faster than you update them? -
Do you have a clear goal for the next 1-3 years and a real plan to achieve it?
Career prospects
You will be able to earn a decent income and secure a stable future for yourself.
Junior Data Analyst + AI Specialist
Middle Data Analyst + AI Specialist
Data Analyst + AI Engineer
Senior Data Analyst + AI Specialist
$600
$700+
$1100+
$1600+
Your path to a dream career
3 months after the start of study
You understand the profession from the inside.
You have your first practical skills, reinforced during practice.
You know what real problems are solved in this position.
You work confidently with the main tools and processes.
You are building confidence that you can work in this role.
You are starting to build your professional network.
You have your first practical skills, reinforced during practice.
You know what real problems are solved in this position.
You work confidently with the main tools and processes.
You are building confidence that you can work in this role.
You are starting to build your professional network.
6 months after the start of study
You confidently solve typical tasks at a junior specialist level.
You have several complete projects (cases) in your new profession.
You understand how to create value for the business in your role.
You have connections in companies and an established professional network.
You enter the job market as a ready specialist, not as a beginner.
You understand what problems you can be paid for.
You can present your value to a company in the language of business.
You have a growth plan for your first year in the new role.
You have several complete projects (cases) in your new profession.
You understand how to create value for the business in your role.
You have connections in companies and an established professional network.
You enter the job market as a ready specialist, not as a beginner.
You understand what problems you can be paid for.
You can present your value to a company in the language of business.
You have a growth plan for your first year in the new role.
One year after study
You fulfill dreams that you previously lacked the money or confidence for.
You live at a pace and standard of living that used to be your goal.
You earn more than before changing your profession.
You feel that you are valued.
You are not afraid to change companies if the conditions no longer meet your expectations.
You take part in solving the team's problems, not just carrying out tasks.
You understand how to grow in your role or move to the next level.
You feel like a full-fledged specialist in the job market.
You have real achievements that you can present to your next employer.
You live at a pace and standard of living that used to be your goal.
You earn more than before changing your profession.
You feel that you are valued.
You are not afraid to change companies if the conditions no longer meet your expectations.
You take part in solving the team's problems, not just carrying out tasks.
You understand how to grow in your role or move to the next level.
You feel like a full-fledged specialist in the job market.
You have real achievements that you can present to your next employer.
3 years after study
You achieve big goals not by luck, but through a systematic approach.
You work at the level of a confident middle or senior specialist.
You earn several times more than at the starting stage.
You choose projects and companies, rather than just looking for a job.
You understand how to create a product and earn income from your experience.
You sell not hours of work, but your value and results.
People turn to you for professional expertise, not just execution.
You understand how to grow your income and influence.
You become a noticeable specialist in your field.
You have a stable career path for the coming years.
You work at the level of a confident middle or senior specialist.
You earn several times more than at the starting stage.
You choose projects and companies, rather than just looking for a job.
You understand how to create a product and earn income from your experience.
You sell not hours of work, but your value and results.
People turn to you for professional expertise, not just execution.
You understand how to grow your income and influence.
You become a noticeable specialist in your field.
You have a stable career path for the coming years.
How to build a dream career
You get to choose among offers, rather than accept the first one that comes along.
Career center tools
- Résumé preparationTaking into account current job market requirements and HR specialists' expectations
- Career webinarsTo discuss the main interview questions and cases.
- 360° SupportConstant contact with a career center specialist on any job placement question
-
Profile auditLinkedIn, HH.ru, Staff.am. We will present your experience in the best possible way. - Q&AWe have collected typical HR questions and prepared answers, ensuring you are fully prepared.
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Course: Interview from 0 to a job offerA special module that prepares you for the interview. -
Job chatGet job openings directly in Telegram, being the first to see them from 3 different sources. -
Guides and checklistsFor preparing for interviews on your own, so you feel confident and without fear. -
Communication with employersGet job openings directly in Telegram from the 3 very first sources. -
Motivation and supportWe are always by your side. We help analyze interviews and strengthen weak points.
What will the career center give you?
You choose, you are not the one being chosen
Where you can build a dream career
Learning path
Speakers and course authors
Rafik Arakelyan
Data Science & AI Specialist
A Data Science, Machine Learning and AI specialist and lecturer with 5+ years of experience, specializing in Python, Machine Learning, Deep Learning, Generative AI, NLP and Computer Vision.
Professional experience at the Central Bank of Armenia, ServiceTitan, Krisp and Yerevan State University. Founder of the NextGenAI educational community and lecturer of Python, ML and Deep Learning courses.
Professional experience at the Central Bank of Armenia, ServiceTitan, Krisp and Yerevan State University. Founder of the NextGenAI educational community and lecturer of Python, ML and Deep Learning courses.
Learning sections
Applying artificial intelligence in data analysis
You will work with modern AI tools, analyzing data, automating processes and creating real applied solutions for business and various industries.
Course program
- The role of data analysis and areas of application
- Examples of analytical questions from business
- The analysis flow: data, analysis, conclusion, action
- General overview of Python and Jupyter Notebook
- Setting up the working environment
- Running your first notebook and core concepts (cell, variable)
- Variable: storing data in named memory
- Core data types: numbers, text, boolean values (true/false)
- Arithmetic operations
- Comparison and logical operators
- Type conversion
- Practical work: calculating price and revenue
- List (list): an ordered sequence of elements
- Tuple (tuple): a sequence of unchangeable elements
- Dictionary (dict): storing data as "key–value" pairs
- Adding, removing and searching elements
- Nested structures
- Practical work: a small dataset of customers and products
- Indexing: finding the position of text elements
- Slicing: selecting a part of text
- Core string methods: len(), split(), strip(), replace()
- Joining texts
- Cleaning text data
- Practical work: standardizing names and categories
- Basics of boolean logic
- Using if, elif and else structures
- Comparison operators and combining conditions
- Writing simple classification rules
- Practical work: customer segmentation by age, purchases and risk
- The idea of iteration and the role of loops
- The for loop and the range() function
- Working with lists and dictionaries in a loop
- The while loop, break and continue commands
- Performing totals, calculations and searches
- Practical work: processing a list of transactions
- The purpose and advantages of a function
- Creating a function (def)
- Parameters and return values
- Local variables and default arguments
- Practical work: writing cleaning, calculation and categorization functions
- Reading and writing text and CSV files
- Working with file paths (pathlib)
- Error handling: try/except
- Connecting external modules (import)
- Structuring a notebook
- Practical work: saving a cleaned file
- The purpose of the NumPy library
- Arrays: shape and data type (dtype)
- Indexing and slicing
- Vectorized calculations
- Core aggregations: sum, mean, minimum, maximum
- Practical work: comparing a loop with a vectorized calculation
- The Pandas library and working with tabular data
- DataFrame (table) and Series (column)
- Loading a CSV file: read_csv()
- Initial data inspection: head(), tail(), info(), describe()
- Detecting missing values and problematic data
- Practical work: initial data quality check
- Selecting columns and rows
- loc and iloc: the difference between the two approaches
- Filtering by condition (boolean mask) and isin()
- Sorting data
- Practical work: answering gradually more complex analytical questions
- Handling missing values
- Detecting and removing duplicates
- Fixing wrong types and invalid values
- Cleaning text data
- A general overview of outliers
- Practical work: comparing data quality before and after cleaning
- Creating new columns: assign()
- Replacing and mapping values: replace(), map()
- Applying a simple apply() function
- Grouping data into ranges (bins)
- Date and time basics (datetime)
- Hands-on: revenue, margin and age group columns
- Why group data
- The groupby() and agg() methods
- Core aggregation functions: count, sum, mean, median, min, max
- Building summary tables
- Hands-on: answering business questions by customer, product and month
- Merging tables: merge() and join
- Appending tables: concat()
- Reshaping: pivot_table() and melt()
- Join keys and common mistakes
- Checking the accuracy of the result
- Hands-on: building one analytical table from several tables
- The goal and workflow of EDA
- Single-variable analysis and distributions
- Exploring relationships between two variables
- Analyzing missing and outlier values
- Documenting observations
- Hands-on: full EDA of a new dataset
- Chart structure: figure and axes
- Line, bar and scatter plots and histograms
- Titles, axis labels and legend
- Visualizing Pandas results
- Making charts more readable
- What the Seaborn library can do
- Chart types: countplot, boxplot, violinplot, scatterplot, heatmap
- Distinguishing data by color (hue)
- Choosing the right chart for the question
- Avoiding misleading charts
- Hands-on: a visual story of 5–6 charts
- Measures of central tendency: mean, median, mode
- Measures of spread: range, variance, standard deviation
- Percentiles and IQR
- Skewness
- How outliers affect the metrics
- Hands-on: statistical comparison of two or three groups
- Core ideas of probability
- Population and sample
- Sampling variation
- Null and alternative hypotheses
- p-value and t-test explained simply
- Practical vs. statistical significance
- Covariance and correlation
- Scatter plots and the direction of a relationship
- Confounding
- The idea of simple linear regression
- Residuals
- Correlation vs. causation: why they are not the same
- Date handling and sorting by time
- Resampling: summarizing data by week or month
- Rolling average
- Comparing time periods
- Defining KPIs and segmentation
- Detecting anomalies
- Defining the project scope and choosing a dataset
- Writing a data dictionary
- Cleaning, EDA and visualization
- Statistical analysis
- Conclusions and limitations
- Independent work with instructor support
- Final quality check of the project
- Building the analytical narrative
- Formulating recommendations and noting limitations
- Reproducibility
- A 5–7 minute project presentation
- Building your portfolio
Packages
MINI
- 24 modules
- 24 interim tests
- 24 additional learning materials
- Individual feedback during the course
- Constant support from the support and service team throughout your studies
- Course completion certificate
- 1 year of access to the professional online community
- 2 cross-industry video workshops with online practical tasks
- 3 universal career webinars on how to pass job interviews successfully
49 200 AMD per month
68 716
BASE
- 24 modules
- 24 interim tests
- 24 additional learning materials
- Individual feedback during the course
- Constant support from the support and service team throughout your studies
- Course completion certificate
- 1 year of access to the professional online community
- 2 cross-industry video workshops with online practical tasks
- 3 universal career webinars on how to pass job interviews successfully
- CV preparation in Armenian
- 1 year of access to a closed Telegram group with job openings
- 1 year of access to the learning platform
- Professional photo for your CV
- LinkedIn profile audit and 2 months of feedback
- staff.am profile audit and 2 months of feedback
65 800 AMD per month
85 938
PRO MAX
- 24 modules
- 24 interim tests
- 24 additional learning materials
- Individual feedback during the course
- Constant support from the support and service team throughout your studies
- Course completion certificate
- 1 year of access to the professional online community
- 2 cross-industry video workshops with online practical tasks
- 3 universal career webinars on how to pass job interviews successfully
- CV preparation in Armenian
- 1 year of access to a closed Telegram group with job openings
- 1 year of access to the learning platform
- Professional photo for your CV
- LinkedIn profile audit and 2 months of feedback
- staff.am profile audit and 2 months of feedback
- 1 individual mock interview
74,200 AMD per month
111 771
Monthly payment with a 12-month installment plan
Frequently asked questions
The Data Analyst + AI course costs, with a 12-month installment plan: MINI package: 49,200 ֏ per month, BASE package: 65,800 ֏ per month, PRO MAX package: 74,200 ֏ per month. You can pay in monthly installments.
The course lasts 6 months.
The format is hybrid: classes are held in Yerevan at 4 Tigran Mets Avenue, and on an online learning platform.
Yes, the course is designed for beginners.
Yes, the academy has a job placement support program. The support depends on the chosen package, for example, profile audits and access to a closed Telegram group with job openings.
Yes, the academy holds free career consultations and helps you choose the right path. Leave a request on the website or call +374 93 12-96-06.
GortsUp Academy is located in Yerevan, at 4 Tigran Mets Avenue. Phone: +374 93 12-96-06, email: info@gortsup.am.
Where to start? We will help
- If you don't yet know what your strengths are;
- If you want a change but can't decide which field to start with;
- Or if you simply want to discover which professions offer decent earnings:
our specialist will hold a Free career consultation and help you choose the right path.
Contacts
GortsUp Academy