Python backend engineering is a flourishing career path training that focuses on the building of robust and efficient server-side applications using the Python programming language. Students will receive classes on Python’s versatility and its extensive ecosystem of libraries and frameworks, such as Django and Flask.

They will have a strong understanding of Python programming, including core concepts, data structures, and algorithms. They will also be proficient in using web frameworks and have a deep knowledge &amp; experience of relational databases such as PostgreSQL or MySQL, including database modelling and query optimization, which is crucial for data storage and retrieval. 

Furthermore, students will be taught on API development and integration using technologies like REST or GraphQL. Gain experience with version control systems like Git and proficiency in writing unit tests as it will be essential for ensuring code quality and maintainability. 

At the end of their training, students can expect to be familiar with various essential topics, including their knowledge of deployment and containerization technologies like Docker and familiarity with cloud platforms like AWS or Heroku, which in turn will enable efficient deployment and management of various applications.

Backend Engineering (Python)

Analytics engineering is an emerging and in-demand career path that combines the fields of data analytics, engineering, and software development. As an analytics engineer, you play a crucial role in transforming raw data into actionable insights that drive data-informed decision-making within organizations.

In this career path, you are responsible for designing, building, and maintaining the infrastructure and systems required for data analysis and reporting.
As analytics engineers, you will work with a variety of tools and technologies, including data warehouses, ETL (Extract, Transform, Load) processes, SQL databases, cloud platforms, and programming languages such as Python. They also collaborate with cross-functional teams to ensure data quality, security, and governance practices are implemented effectively.

In addition to technical skills, analytics engineers possess strong problem-solving, communication, and collaboration abilities. They have a deep understanding of data structures, data modeling, and analytics techniques. They continuously stay updated with the latest advancements in data engineering and analytics tools to deliver innovative and scalable solutions.

Analytics Engineering

Cloud DevOps engineering is a dynamic and rapidly growing career path that combines expertise in cloud computing and software development practices. DevOps engineers specialise in bridging the gap between development and operations teams, enabling efficient and continuous delivery of applications and services. 

During this training, students will learn how to leverage cloud platforms and tools to automate infrastructure provisioning, deploy and manage applications, monitor performance, and ensure scalability and resilience. They will develop a diverse skill set and receive support in getting certificates in cloud platforms like AWS, Azure, or Google Cloud, proficiency in scripting and automation, knowledge of containerization technologies such as Docker and Kubernetes, and strong problem-solving and troubleshooting abilities. With the help of our instructors.

By the end of this training, students can expect to be familiar with various key topics. Firstly, they should have a strong understanding of cloud platforms, including services such as virtual machines, containers, serverless computing, and storage solutions. They will possess knowledge of infrastructure as code (IaC) tools like Terraform or CloudFormation to automate infrastructure deployment. Proficiency in configuration management tools like Ansible or Chef will enable them to manage software configurations effectively. Additionally, they will gain expertise in continuous integration and deployment (CI/CD) practices using tools like Jenkins or GitLab. Students can expect a combination of theoretical knowledge and hands-on practical experience to prepare them for real-world scenarios in cloud-based development and operations.

Cloud DevOps Engineering

This Career Path's goal is to train students to be young professionals in the field of data engineering. In this career track, students will first learn the fundamentals of python programming, SQL, version control and test driven development.

Furthermore, Students will be exposed to the process of designing, building, maintaining scalable and reliable data pipelines using both open source and AWS specific services. This will help students understand the significance of data security and governance in the data space.

Adebisi Abiodun

I have better understanding, exposure, and now know how to look for a way to solve most problems in data engineering.

Abdusalam Fatai

Data2Bots Academy is all you need to become a professional Data Engineer. They provide real time classes, good support system and opportunities to jobs and internship after your program. I will recommend Data2Bots academy any day, anytime.

Adeoye Abiola Solomon

As a person who's a self-taught developer it's very easy to learn a lot of things that don't need learning at the early stage of my career and skip a lot of important things that need to be known, but with the data2bots data engineering beginners module, you'll learn everything you need to know to get that entry into data engineering, I can say this for a fact because I've been on the path to becoming a data engineer for a while but was always confused with how to approach it although I had an idea of the roadmap. So far the academy's roadmap is clear and has touched all the basics one needs to become a data engineer, it even cleared up my misunderstanding on some software principles.

Franklin Chibueze

It's been an amazing journey so far, seeing my dream coming to pass. The methodology of teaching is student-friendly and it also enlightens me on how to use data engineering technologies and applications.

Career Paths