Main advantage: better Python usage in your company, so that developers work faster and write better code, that is easier, faster and cheaper to maintain
Duration: 3 days x 7 hours brutto (i.e. including breaks) + consultations after every course day
Format: workshop (70% workshop / 30% lecture)
Venue: client’s office or other place chosen by the client, in Europe
Enrollment: in-house on-site course for a group of people within one company
Group size: max 10 delegates
Course language: English or Polish or both during the same training
Audience: Python developers, team leaders, architects, analysts, DevOps, R&D, testers
Audience requirements: intermediate or advanced Python knowledge and experience
- Intermediate Object Oriented Programming
- __str__ vs __repr__
- __str__ Method vs str() Function
- Classes Imitating Functions with __call__ Special Method
- Encapsulation – Interface vs Implementation
- Protected Attributes
- Private Attributes
- Read-Only @property
- Read-and-Write @property
- Introducing Encapsulation to an Existing Class without Breaking the Interface with @property
- Variable Annotations
- Dataclasses: Usage, Default Values, Default Values Trap, Default Value Factory, Fields Customisation, __post_init__
- Introduction to Single Inheritance
- Attribute Lookup Mechanism
- Code Reusage with Inheritance
- Method Overloading
- Advanced Object Oriented Programming
- Special Methods Recap
- object Class
- defaultdict Data Structure
- Inheriting from Builtin Classes, i.e. Data Structures
- Alternative Constructors with @classmethod
- Bound vs Unbound Method
- Including __dict__ in Slots
- Abstract Base Classes
- Multiple Inheritance: Fundamentals, MRO (Method Resolution Order), Diamond Problem, super() Behaviour
- Mixin Classes
- Metaclasses: type Metaclass, Writing Your Own Function-based and Class-based Metaclasses, Use Cases, Simpler Approaches
- SOLID Principles – We discuss SOLID principles that makes code easier to read and maintain. This part is supplemented with exercises showing how to apply (and how not to do this) SOLID in Python. This will be helpful in the second step of each iteration in TDD (as well as BDD), that is writing production code.
- Introduction do Design Patterns
- Design Patterns Objectives
- Creational Patterns
- Factory Method
- Abstract Factory
- Structural Patterns
- Behavioral Patterns
- Template Method
- Chain of Responsibility
Benefits for the Sponsor
As the course sponsor or HR you get:
- Analysis of the needs and my help to choose or design a great course during a phone call with the sponsor, HR, team leader or/and course delegates. On top of that, we ask delegates on the very first day what their needs are, to make even better usage of the course time.
- Course customisation to your needs.
- Guarantee that the course is conducted by an expert that worked for Google.
- Course evaluation as an electronic form at the end of the last course day. The evaluation results are sent to interested people (most of often they’re course sponsor and HR).
- Simple communication – you can contact the trainer directly by phone or email.
- Easy buying procedure – one call or email is enough to get offer and to book a date. I don’t do overbooking. The course is confirmed once you send the Purchase Order.
- Friendly business partner – as a rule, I treat all my clients like friends. I don’t build walls, I’m not pretending to be a huge training company and I write in first person.
Clients very often decide to order other training (including dedicated courses) after observing positive results of this course.
Benefits for Delegates
Delegates will benefit because of:
- Seven hours course every day (including breaks)
- Consultations after every course day.
- Support after the course, via email and phone.
- Setup instruction before the course to save time at the beginning of the course. I’m happy to help you via email, phone or Skype, zoom.us etc. in case of any questions or issues.
- Course materials consisting of code snippets, comments, exercises and solutions. The entire courseware is a single web page which make it very easy to lookup something there. Courseware is available online during and after the training. Delegates can download it to use it offline. Courseware can be updated during the course in real time, so that we can include comments or entire new sections suggested by delegates.
- Environment ready to use after the course – we don’t use virtual machines. Instead, we install everything on delegates machines, so that they can reuse the same setup after the course.
Below you can find some references.
Very inspiring training. I really appreciate the way Chris managed to walk us through the complex world of machine learning using Python. Good course materials updated real time. Highly recommend.
Finance Director at DNB Bank Polska S.A.
Well prepared training and reasonably passed knowledge, thanks to which we develop better services.
Infrastructure Team Manager at allegro.pl
Chris recently taught a four day class on Machine Learning with Python four our team. The class was very good with the right balance of theory and practice. I cannot think of a better way to give a four day class about such an extensive topic.
Head of Krakow Product Control Analytics at HSBC
You can read more references here.