Learn Data Analytics using Python Programming Language

Data Analysis and Visualization Classes in Surulare, Lagos, Nigeria
Duration: 3 Months (3 Times per Week)
Classroom Training: Monday, Tuesday and Thursday
Online Training: Flexible Days and Timing

Classroom Training: ₦350,000
Online Group Training: ₦450,000
Home Training: The cost depends on your location
One-on-One Online Training: ₦700,000
Home Training: Cost depends on your location

Programs Included in Diploma in Data Analytics

  • Introduction to Python: What Is Python, Installing Python, IDLE & Python Shell
  • Variables and Assignment Statements
  • Built-in Functions
  • User-Defined Functions
  • Conditional Logic: if, else, and elif Statements
  • Loops
  • Lists
  • Strings
  • File Input/Output
  • Internet Data: API
  • Data Structures: Tuple, Lists of Lists and Dictionary
  • Object Oriented Programming (OOP): Principles of OOP
  • Introduction to Python Web Development using Django
  • Introduction to Data Analysis
  • Python for Data Analysis using NumPy
  • Python for Data Analysis using Pandas
  • Introduction to Data Visualization
  • Python for Data Visualization using Matplotlib
  • Power Bi or Tableau
  • SQL
  • Microsoft Excel
  • Working with CSV Files
  • Data Mining
  • Project

Data analytics is the science of analyzing raw data in order to make conclusions about that information. Many of the techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption.

Understanding Data Analytics

This course gentlly introduces students into the concepts of data analysis, the role of a Data Analyst, and the tools that are used to perform daily functions. You will gain an understanding of the data ecosystem and the fundamentals of data analysis, such as data gathering or data mining. You will move on to learn the soft skills that are required to effectively communicate your data to stakeholders, and how mastering these skills can give you the option to become a data driven decision maker.

Data analytics is a broad term that encompasses many diverse types of data analysis. Any type of information can be subjected to data analytics techniques to get insight that can be used to improve things. Data analytics techniques can reveal metrics and trends that would otherwise be lost in the mass of information. This information can then be used to optimize processes to increase the overall efficiency of a business or system.

For example, manufacturing companies often record the runtime, downtime, and work queue for various machines and then analyze and visualize the data to better plan the workloads, so the machines operate at optimal capacity.

Data analytics can do much more than point out bottlenecks in production. Gaming companies use data analytics to set reward schedules for players. This helps the firms keep the majority of players active in the game. Content firms use data analytics to keep their target audiences clicking, watching, or re-organizing content to get another view or another click.

Data analytics is important because it helps businesses optimize their performances. Implementing it into the business model means companies can help reduce costs by identifying more efficient ways of doing business and by storing large amounts of data. A company can also use data analytics to make better business decisions and help analyze customer trends and satisfaction, which can lead to new and better products and services.

Who Data Analytics Course Is For:

Our Data Analytics training is for programmers and aspiring ones, who are interested in analysing and visualizing data, to enable them make critical decisions.


  1. Basic computer knowledge is required as a prerequisite. The Data Analytics course assumes the aspiring student already has a basic knowledge of computer usage, but no prior programming skill is required.
  2. Your willingness to learn Data Analysis and Visualization (Data Analytics) using Python Programming Language
  3. Your own laptop! FlamyTech strongly recommends that each programming student comes with his/her own laptop, to enable the learner practice at home. In programming, everyone agrees that practice makes perfect!

Why You Should Learn Data Analytics:

The concept of “big data” may have been around for a while, but the last few years have seen a sizeable swell in interest and media attention. Extremely recently, firms such as Cambridge Analytica and the way in which social media companies use the data collected about their users have hit the headlines and raised awareness even further of the enormous impact big data has on our lives every day. We looked into what it’s actually like to work in big data and why students should specialize in the field.

Below are the reasons why you should choose Data Analytics, as a career path:
  • Big data is here to stay, which means career longevity is highly likely
    The big data industry is growing globally at a great speed, with nearly 2.3 trillion gigabytes of data produced every day, and the data galaxy doubling every couple of years. So, the ability to make sense of all this data and use it to change the way we live and interact with one another is set to inevitably become a vital part of business.

    With a predicted growth of US$7.3 billion this year, the market size for big data is expected to soar past the US$40 billIon mark over the next few months, which is why a new generation of trained data experts and analysts are needed to lead the way and establish better data governance to win over consumers. You could be one of them, by learning Data Analytics at FlamyTech Computer School.

  • You’ll use data in all sorts of amazing ways to change the world
    Several business sectors have already demonstrated the potential of what can be achieved through data analytics. Some NGOs, for example, have been using artificial intelligence to fundraise by collecting data on their supporters and using this to predict and target actions and messaging which are most likely to resonate with different types of donors.

    In sport, analysts have been a regular feature for several years now, using statistics in their operations both on and off the pitch in order to make better scouting decisions and monitor their players’ health, fitness and nutrition.

    Some teams, such asFC Bayern Munich, have even been using data to inform their game plan. In 2014, the German national team gained a competitive advantage over other teams by using sports analytics software to research opponents’ performance, including average ball possession, number of ball touches, distance travelled, positioning and speed of passing. Information on the upcoming opposition and bespoke feedback on their own performance was then sent to each player via an app on his smartphone.

    In the healthcare sector, hospitals have been collecting reams of health data to enhance patient care. In fact, 47 percent of hospitals in the US are already using predictive analytics to minimize costs and predict operating room and staffing demands. Some experts even believe that big data will enable hospitals not just to cure disease, but also to prevent it in the future.

    Among them, Lloyd Minor, dean of the Stanford School of Medicine, said:
    By leveraging big data and scientific advancements while maintaining the important doctor-patient bond, we believe we can create a health system that will go beyond curing disease after the fact to preventing disease before it strikes by focusing on health and wellness.

  • There’s a growing skills gap for trained big data experts
    If these types of job roles sound intriguing, we’ve got good news. Big data jobs will grow by 4.4 million by 2024, according to the US Bureau of Labor Statistics, and there’s a widening skills gap in the sector. According to a 2014 survey, 41 percent of businesses cited a lack of skilled candidates as a major challenge to integrating big data into their operations.

    Job prospects are good in the sector, with data analysts earning on average €41,329 (US$51,320) in Germany, £25,511 (US$32,930) in the UK, and CHF88,049 (US$92,838) in Switzerland, according to PayScale. In Nigeria, the average starting salery of a data analyst is ₦250,000 and grows with time, based on competence.

  • The range of jobs available with a degree in Data Analytics is huge
    If you pursue a career as a data analyst, the first thing to get straight is that your role isn’t the same as a data engineer or data scientist. These roles work on the technical side of data mining and data storage, whereas data analysts pull relevant bits of information from enormous databases in order to inform decisions in a number of business areas like HR, marketing, customer service and operations.

    A course in data analytics would impart you with important transferable skills, such as project management, critical-thinking and problem-solving, and open up opportunities across industries as data managers, data consultants, consumer and market knowledge managers, chief data officers, big data architects and business and marketing analysts.

Job Prospects:

By adding Data Analytics to your resume, you stand out to land a very lucrative IT job in a big corporation.

And the Job Opportunities include, but not limited to:
  • Python Developer
  • Software Developer
  • Software Engineer
  • Research Analyst
  • Data Analyst
  • Data Scientist

A Diploma Will Be Given Upon Course Completion

After successfully completing the Data Analytics course at FlamyTech Computer School, the Management would award you a Diploma in Data Analytics. Please, note that FlamyTech is duly-registered in Nigeria with RC: 1195702. So, never worry, because the diploma we award is recognized.

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Diploma in Android App Development
Diploma in Oracle Database
Diploma in Back-end Web Development
Diploma in Full Stack Web Development
Diploma in Front-end Web Development
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