Use Python in data analysis!
A course from scratch that shows you how to analyse data and how to use machine learning in your everyday work
Popular tools, lots of practice, practical skills!
Topics:Analyst's work environment (Anaconda, Jupyter Notebook), data processing (NumPy, pandas), data acquisition from various sources, preparation and data cleaning (working with Series and DataFrame), data analysis, visualisations (Matplotlib, Seaborn), statistical analysis and inference, prediction and classification thanks to scikit-learn
Application:management, banking, insurance, telecommunications, industry, trade and services, health care, public administration
Duration:80 hours for the course + 40 hours working at home with our materials = 120 hours in total
- weekends (Sat-Sun, every 2 weeks on average)
- day classes (a 4-day block and two 3-day blocks)
Group Size:When on-site classes are allowed - a maximum of 9 people in the room
(more space per person than recommended).
For remote courses - up to 17 people in total.
Enrolment:Course from scratch
Location:Warsaw, Krakow, Katowice, Gdansk, Poznan, Wroclaw and remotely (online live with an instructor and the group)
Flexibility:a) you can resign up to 15 days before the start of the course
b) during the course you can:
- switch from on-site to remote learning
- switch from remote learning to on-site
- cancel course participation and finish later
(subject to availability).
Data analysis and the Python language
Drawing conclusions from available data is increasingly becoming the primary method of decision-making. Until recently, only large analytical companies were hired for this purpose, and only the largest market players could afford their services. The emergence of simple (and often free) tools for data analysis makes it possible for any company or individual to apply the same methods.
You just have to learn them.
Accessible, ready-made solutions for machine learning have allowed even novice analysts to skip the tedious process of searching for hidden regularities and therefore achieve results previously only available to experienced statisticians. As a result, you don't need to be a specialist to process more data and draw more accurate conclusions from it, and you can achieve results faster than if it was done by a human.
Python is one of the most popular languages for data analysis thanks to a wide range of ready-made libraries. It is also very easy to learn, so writing your own dedicated tools is not a problem even for novice programmers.
- Pandas is a library for manipulating data in the form of tables or sequences. It allows you to quickly and easily combine, split and transform data to draw conclusions from it.
- NumPy is a library for scientific computing. It is written in C, therefore it runs much faster than code written in Python and it is easy to use. Complex calculations can be done with a single command!
- Matplotlib is a library for data visualisation, i.e. drawing graphs. With a few commands we can create any graph, and then display it or save it to a file.
- Scikit-Learn is the most popular machine learning library. It is not as powerful as Google's TensorFlow or Facebook's PyTorch, but its ease of use, openness and the many algorithms available, make it the first choice for most analysts using Python.
- Python is a very universal language. Apart from analysing data, it allows you to easily download, process and export it both as a report and as an input file for other applications (e.g. Excel).
This course, starting from scratch, will teach you how to use packages dedicated to data analysis in Python. You do not need to be able to program or know Python (although you will get more out of the course if you know the basics of programming).
During the course, we will focus on learning about data analysis tools, not on Python itself. We will go through just enough of it to get to grips with using the tools. This is not a programming-only course, so if you want to learn how to write programs and read code freely, you can also take our Learning to Program in Python course or our short course Scripting in Python, but this is not required to get started. Knowledge of Python will give you a better understanding of these tools, but is not necessary if you want to learn how to use them. You do not need to be a professional programmer or have experience in data analysis.
This is not a mathematics lecture, but a practical course
We do not focus on teaching theory - we pass on practical knowledge. This is not a university lecture, we will not go through the mathematical basics of the models used, we will simply teach you how to use them! You will learn the work of an analyst - preparing, analysing and interpreting large amounts of data, using the Python programming language and its add-ons. During the classes you will practice the techniques you have learnt on real data sets, similar to those you may encounter in your profession.
What will you learn during the course?
make use of a data handling environment with the use of Python (Anaconda, Jupyter Notebook)
process data using NumPy and pandas
obtain data from various sources, prepare and clean data
prepare visualisations using Matplotlib and Seaborn packages
you will learn the basics of data analysis and statistical inference
you will understand how machine learning works and when to use it
This is a wide range of material – delivered in a simple and accessible way. The course programme is structured in such a way so that it can convey in 10 days the basics of data analysis using the Python language and its add-ons.
In the case of an on-demand training for your company, it is possible to adapt the programme and duration of the course individually – e.g. starting with an introduction to Python or covering more advanced topics related to data analysis.
After completing the course, you will receive a certificate signed by ALX with a detailed list of your acquired skills. Each certificate has a unique identifier and an electronic version (regardless of whether the paper version has also been ordered). If you wish, you can share your certificate by pasting its URL – for example to your profile on a social or professional network or into your CV.
Who is this course for?
For people who want to work in data analysis.
The programme of this course is arranged in such a way that most of our students can start working in data analysis using the tools we present immediately after completing the course, or even during the course.
For people who use Python on a daily basis and want to develop their skills.
This course improves your professional skills and opens the way up to a promotion or a better job!
For managers, executives and business owners
Access to current and accurate analysis is the key to making the right business decisions.
What do you need to know before the course?
Everyone is welcome to the course. Any knowledge of the basics of Python programming is welcome, but absolutely not required. If you are unfamiliar with Python, you will learn all the needed commands during the course. If you know Python, you will practice functions and data structures useful in data analysis and you will also understand better the operation of the discussed tools. If you want to learn programming first, you can take a look at our offer – the longer bootcamp Learning to Program in Python or the short course Scripting in Python.
No experience in data analysis is needed.
No programming experience is needed.
How do we teach?
We focus primarily on practical classes! The course is organised in the form of workshops - this means that there are no lectures like there are at university. We work in small groups, with an instructor at all times. All course modules are filled with practical exercises. Our instructors will present you with a set of the most common problems that arise in real business conditions when working with data - you will see for yourself how important and unique this knowledge is.
Learning at home
The course is 80 hours long and it is very intensive, but you can and should get even more out of it! How to do this? You need to make the effort to study at home as well. Our instructors always encourage you to work independently at home, preparing interesting tasks which you work on in between classes. A large number of exercises will make you consolidate the acquired knowledge and master the technology very quickly. If you have a problem with a task you can always contact your instructor.
Is bootcamp a big expense?
Spread it out in installments at no additional cost.
Participation in the bootcamp is an important investment for many of our students. It is an investment in your skills and a chance to get your dream, well-paid job in the IT industry.
It is also a considerable expense!
We know this and that is why we offer convenient fees for our bootcamps in an installment system without any additional costs.
You pay only as much as the course costs.
How to pay for bootcamp in installments?
The process is very simple - you do not have to contact any bank, you do not need to undergo complex verifications, you only need an ID document - you handle everything with our company. Check it out >>
Read what our customers say about our work.
The training was conducted at a high technical and organizational level and the involvement of the organizers deserves high recognition.
The participants of the course highly rated the training program, teaching materials as well as the competences and commitment of the lecturers. (...) We recommend ALX as a partner guaranteeing the proper performance of the service.
We are very pleased with the organization of the training. All trainings and trainers received high marks in surveys from our employees.
The implementation of the training program was highly appreciated by the course participants. ALX can be recommended as a reliable business partner in the field of IT training, with a staff of lecturers with extensive experience.
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Weekends - classes take place every other weekend on Saturdays and Sundays, from 9AM to 5PM (8 hours per day, including a lunch break and two shorter coffee breaks). The course consists of a total of five sessions.
Day classes - the course consists of a total of three blocks (4 days + 3 days + 3 days), 8 hours per day, including a lunch break and two coffee breaks (9AM to 5PM). There is a longer break in between the teaching blocks that lasts usually a week or two.
Evening classes - classes take place from 6PM to 8:30PM, the duration of the course is around 3 months, classes are held on Mondays and Wednesdays or Tuesdays and Thursdays every week.
In the weekend and day class types, the whole course consists of a total of 80 hours of classes. The weekend variant is around 2 months long. The day class variant is the most intensive and takes just over a month to complete. The evening class variant consists of 65 hours due to the lack of longer lunch breaks. This type of course is the slowest and takes the longest to complete – around 3 months.
Remote learning – Virtual Classroom, live with the trainer and the group.
The form of remote classes (videoconference, “virtual classroom”) is the same as our standard mode classes just without leaving your home or office. The classes are live-streamed with the instructor teaching them instead of watching any pre-recorded videos. The instructor explains everything, helps with any problems and is very engaged with the group. Classes are taught by the same people who teach the standard on-site classes from the same program.Participants can count on the instructors help but they are also engaged with other students just as they are during on-site courses. We take great care to maintain the workshop nature of our classes.
In practice the actual course looks like this: the participant receives an invitation with a link which will connect him/her remotely to a specialised teleconference system, creating a "virtual classroom". The participant will be able to see the instructor and the image from the overhead projector. The class duration will be the same as the on-site classes. During the classes, in addition to vision and sound, there will be access to a chat (with the instructor and the other course participants). There will be the possibility to send files/attachments, show parts of the code, ask questions, receive help, etc. At the participants request, the instructor can also get access to the screen and mouse of the participant’s computer (“taking over the mouse and keyboard”) or the window with the code in the programming environment in order to correct a line of code, make comments or simply to show how to perform a given action.
After completing the course, you will receive the same certificate (regardless of the type of class) and the instructor will be available after the teaching block to answer any additional questions.
Remote weekend (part-time), day (during the week) and evening class (during the week) dates are available. There is the exactly same number of teaching hours during remote learning as there is during on-site classes and classes are held at the same times.
- Analyst working environment
- Conda package manager
- Pip Manager
- Creating a virtual environment
- Jupyter notebook
- Elements of Latex notation
- Data processing
- Introduction to NumPy
- Creating vectors and matrices
- Transformations, operations in NumPy
- Elements of arithmetic and algebra using NumPy
- Solving linear equations
- Introduction to Pandas
- Series and data frames
- Retrieving data from different sources
- Online resources
- Data preparation and cleaning – Operations and transformations DataFrame
- Deleting columns and rows
- Dimensional changes – reshaping
- Ranking and sorting data
- Combining frames (concatenate, merge, join)
- Introduction to NumPy
- Data analysis
- Introduction to matplotlib
- Graph generation from within pandas
- Seaborn and other tools for data visualization in Python
- Basics of statistical analysis
- Statistical inference
- Introduction to machine learning.
- Overview of machine learning methods and algorithms
- Breakdown of machine learning methods
- Supervised learning
- Unsupervised learning
- Breakdown of machine learning methods
- Machine learning process
- Data mining
- How to choose the best model for the task
- Data preparation
- Learning dataset
- Test dataset
- Model training
- Model validation
- Model overfitting
- Techniques for data-dimensionality reduction
- Overview of machine learning methods
- Linear regression
- Polynomial regression
- Logistic regression
- Data grouping
- Dimension reduction
- Artificial Neural Networks
- Combining classifiers
- Visualizing the results
On-demand training costs and registration
The prices provided in the general tables cover the cost of an open (public) training for one person.
In the case of an on-demand training at the Customer's premises, you are required to provide the necessary facilities (room, computers, projector) and we will send an instructor to run the training. The price for a session is calculated for the whole group.
The cost does not change significantly along with the number of participants. There is no minimum number of participants but we recommend no more than 10-12 people because the training becomes much less effective with a bigger group..
The cost of an on-demand training consists of:
- the base training cost, plus
- travel and accommodation charges for the instructor
The base price of an on-demand training varies, but it is usually around the price of an open training for 3-5 persons (regardless of your group size).
The typical travel and accommodation price for the EU/Schengen zone is under 1250 GBP (1500 EUR) for a 5 day session. We do our best to keep it as low as possible in your location.
The payment can be in GBP or EUR, whichever you prefer. The quotation we will send you with the exact amount in your currency will be valid for 3 months, regardless of any changes in the exchange rate.
For more information, or to register to a group, please contact us at email@example.com and tell us know:
- the course(s) that you are interested in,
- your location,
- your preferred dates,
- the number of people you wish to train,
And any other questions that you may have.
We can also customise the training program of any of our trainings (or create a new one) according to your needs – whether you want to focus on particular solution used in your company, include material concerning a technology we do not usually cover, or create a tailor-made training.