Machine Learning: What is it and what are its applications?

Big Data and Machine Learning are among the most talked-about concepts in the world of tech today. However, the average person would seriously struggle to actually define what they mean or what a Machine Learning course would entail.

At Ubiqum Code Academy, we have a specialized course in Machine Learning and Data Analytics, and in this short article, we’ll tell you what Machine Learning is and how it is used in data analysis.

Machine learning course mentors with participants

One of the common definitions goes something along the lines of: “Machine learning, or automated learning, is a branch of artificial intelligence that allows machines to “learn” from data analysis to identify patterns and support decision making with minimal human intervention”.

At Ubiqum, we think this definition is rather abstract and inaccurate.

Firstly, because machines do not “learn”. They are lifeless instruments that execute very complex calculations very fast, but everything they execute has been programmed by humans. While machines now can compile code and make minor adjustments, we’re still far from a computer that “self-programs” itself, in the sense that it consciously identifies issues and alters the code of its programs according to its own experience, something that the human mind and memory do.

In any case, what is certain is that software engineering, together with the power of today’s computers and the enormous amount of digital data available have given rise to complex programs that allow us to process and analyze a huge amount of data efficiently. This method was out of reach for even the top tech companies just a couple of decades ago but nowadays, it has utterly revolutionized the way we do business.

So, to help decipher how things are today, we’ll start by describing the three general profiles that outline Machine Learning, Big Data, and Data Analytics:

1. Machine Learning Engineer.

First of all, we need people who develop algorithms. These algorithms are very complex software programs and require a great deal of specialization. A MLE, as described here, is a software engineer on steroids, so it’s no wonder they have about 10 to 15 years of work experience and possibly a PhD that focuses on new Machine Learning algorithms.

2. Data Engineering

Secondly, we need people who deal with the data collected by corporations and government agencies. This role has existed in some form since humans began interacting with numbers, but a Data Engineer in a systems administration department has become an incredibly intricate, sophisticated role over the last 20 years. This profile is still very technical and excels at dealing with new products related to database administration.

3. Business Data Analyst

The third profile encompasses those who leverage data to improve businesses. At Ubiqum, this is the profile we specialize in through our Data Analytics & Machine Learning course. These skills will soon be expected and essential for any business leader, and they are a great springboard to move on to more advanced roles.

Throughout all of these profiles, Machine Learning plays a major role in processing large amounts of data and obtaining results that help improve all kinds of businesses.

Students from the Ubiqum machine learning course

How and when are Machine Learning algorithms used?

Machine Learning algorithms are an integral part of a more complex process — the business data analytics process, or CRISP-DM, the Cross Industry Standard Process for Data Mining.

This process consists of the following steps:

  • Formulating the business challenge for data analysis
  • Curating, cleansing, and structuring datasets
  • Conducting preprocessing procedures on the dataset. Exploratory Data Analysis and Feature Engineering usin Python and R.
  • Implementing Machine Learning algorithms to model the problem
  • Analyzing outcomes and refining the model through iterative training of the model.
  • Translating findings into actionable insights for business applications

In this broader context, we can see that understanding how to use Machine Learning algorithms is necessary to become a professional data analyst, but it’s not everything. It is just a very important piece of the whole process.

Data analytics and machine learning course participants

Ubiqum Code Academy: Beyond The Traditional Bootcamp.

Since our establishment in 2016, we’ve undergone a significant evolution. Initially employing a conventional bootcamp format, where cohorts of 10  to 20 individuals progressed collectively, we’ve transitioned to a more adaptive and personalized model. Our primary objective is to cater to the diverse time commitments of our students by offering a bespoke mentoring service.

Our methodology is centered on real-world, very structured projects,  designed to simulate the challenges professionals encounter in the business and corporate realm. This approach is further bolstered by the support and guidance from a dedicated personal mentor, coupled with the flexibility embedded within our program schedules.

We Keep

  • Intensity. Our courses cover extensive content within a short duration, allowing for rapid progress.
  • Focus. We prioritize delivering highly specific and market-demanded content for tangible skill enhancement.

We Add

Personalisation: A dedicated personal mentor available throughout the course, providing one-on-one guidance.

Flexibility: Customized timetables and dedicated support tailored to each student’s requirements.

Practical and Professional : Emphasis on real professional practice over extensive theory, ensuring hands-on, industry-relevant learning experiences.

We Eliminate

Fixed Timetables: Uniform schedules applied to all participants.

One Teacher for Multiple Students : Single instructor managing multiple students simultaneously.

Rigid Start and End Dates: Firmly set commencement and conclusion dates for the course.

Explore Ubiqum’s Data Analytics Courses

We provide three distinct career paths tailored to suit different student’s profiles.

  1. Data Analytics and Machine Learning: This main program prepares students to start as junior Business Data Analysts in the field. It’s suitable for anyone looking to kickstart a career in this area.
  2. Data Science and Deep Learning: An advanced program designed for students with a solid technical background (STEM) who want to delve deeper into the field of data science.
  3. Data Analytics and Power BI: Tailored for students inclined towards business aspects rather than the technical complexities. It focuses on mastering data management, modeling, and expertise in Business Intelligence using Power BI.

All our students attain proficiency in Python, SQL, modelling, and commonly used Machine Learning algorithms regardless of the chosen program.

Want to know more about our Data Analytics Courses?

We trust that this concise information has shed light on what you can anticipate from our bootcamp and how it will assist you in growing within the realm of Data Science.

For more information, fill out the form below and one of our career advisors will contact you with the complete syllabus and any further information you need.

Experience firsthand the Data Analytics Course at Ubiqum by taking advantage of our two-week free trial.

This trial allows you to immerse yourself in the course before making a formal commitment to enroll.