What do you have to know in order to become a data scientist today?
Ask yourself, do you really want to become a data scientist? If you’re working but the nature of the work pisses you off, this is the new opportunity for you. If you’re a student still in college or university, but you don’t know which career to choose, this is the best opportunity for you.
This is the age of technology and life is fast growing. Many things are becoming obsolete, and new inventions are replacing them. However, no matter how fast technology is growing, people are also carving their niche to the opportunities involving round it. What are you doing to be part of the leading world?
Data science and Artificial Intelligent are now leading the profession in the world of technology. People are not majorly rushing to the niche, but the entire lives will depend on data in the few years to come. Data science is the job that can earn you up to $2000 monthly. Oh, did I say “can”? a friend is already earning $1500 monthly as a data scientist. Life depends on data and data is now the world.
On the contrary, Data Science and Artificial intelligent are the branches of Machine Learning. What do I mean? Machine Learning is the connection between data science and Artificial Intelligence since Machine learning is the process of learning from data over time. Though, it’s not the thing connecting them together. But, machine learning is the branch of Artificial Intelligence that works best with data science.
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Artificial Intelligence focuses on understanding core human abilities such as vision, language, speech, decision making, and core compound and complex tasks. However, Artificial Intelligence, in its present are complex, but no human intelligence near it. Know it today that, Artificial intelligence will soon take over all human daily activities. Will you be left out when the time comes?
It can be precisely said that data science and artificial intelligence are bound together by data.
How do you launch your career as a Data Scientist?
There are varieties of positions that fall under data science. I categorized into two:
- Business Data Scientist, and
- Product Data Scientist
Well, there are core skills needed by every data scientist. Also, some roles require the skills from both the business and the product side. I will not bore you with the list of irrelevant things or things that are not needed for now. The goal is to give you core skills within the two categories that will give you biggest bang for your buck.
We only have 24 hours in a day. You will have to eat, sleep, go to work (if you’re working class), go to school (if you’re still a student), and spend time with friends and family. I’ve considered those factors. Just be listening to me as I’m bringing the core skills into your doorstep.
There are different requirements from the employers, nut if you note down the following core skills, you will land a high-paying job in the field. If you didn’t, NEVER FOLLOW MY INSTRUCTIONS AGAIN!
Below are the core skills needed to launch your career as a data scientist.
- Exploratory Data Analysis (EDA): This is also known as “Data Analysis or Exploratory Analysis”. All you need is to analyze and extract data insight for your model. You will do this before your modeling or building your product. this includes data visualization and calculating the key summary statistics. A proper exploratory analysis will guide you through the rest of your project.
- Data Processing: This is an act of cleaning, extracting, transforming, aggregating and de-aggregating data. However, this is the transforming of data or developing of raw data into a meaningful and useful format for analysis
- Applied Machine Learning: Machine learning involves data exploration and cleaning, algorithm selection, feature engineering, and model training. It doesn’t matter if you are modelling or not. Machine Learning is one of the central technology within the field.
Business Data Scientist: core skills needed to launch your career as a data scientist.
The business data scientist is the first category as a career in data science. What does Business data Scientists involve?
Business data scientists are meant to improve business growth and profitability through data analysis, predictive modeling and training and testing of a dataset. Another keyword comes in: “Dataset”. You will get to know what it means as you continue the course. You as a business scientist, the major tasks ahead of them is to emphasize on the insight that you derive from the available dataset.
- Marketing: Marketing is one of the major tasks for a business data scientist. It’s the building predictive model and bidding strategies for ad markets like Facebook Ads or Google Adwords.
- Strategy: This is using one of the algorithms called “Clustering” to find a similar test and control store for a chain-wide experiment.
- Investing: this is the using stock price, mini and macroeconomics indicators, and machine learning to predict stocks
- Operations: Using some algorithms to build a model that predicts customer choice, the number of goods that can pull out in a day and how companies proactively reach their potential customers.
To be a business data scientist requires more core skills rather than those stated before. The following skills are expected to note:
- Communication and Presentations: As a business scientist, getting the right data-driven solution is not the only solve the problem, but communication and presentations are the other half of your problem-solving. For instance, after you’ve perfect your model, did your predictive analysis correctly and you’re to present your work to the stakeholders or committee or at a conference, then communication issues arise. Remember all your solutions are in either “Graph or chart”. 90% of the people present may know nothing about what you’re showing on the screen until you speak in the language they understand. So, as a business data scientist, you must have communication and presentation skills.
- Domain Knowledge: Programing or data science skill is not enough to become a business data scientist. You’ve to apply other skills like marketing, finance etc, to arrive at real business value. Having other skills in business-related will definitely help your career as a business data scientist.
Product Data Scientist: Core Skills needed to launch your career as a data scientist.
A product data scientist is the second category of how to launch a career as a data scientist. Product data scientists are more of a software building to solve human problems. A product data scientist will build a Machine learning or Artificial Intelligence software or tools. They will train model, build a prototype, and integrate Machine learning solutions into other parts of the software. As a product data scientist, your core task is to build your product.
- Entertainment: If you’re a fan of music or anything related, you can build a recommendation engine to recommend other music or movies for the user.
- E-commerce: e-commerce is one of the sophisticated niches in woo commerce and has millions of people transacting daily. Building and integrating a dynamic pricing model into an eCommerce platform.
- Banking: Data scientist is seriously making theirs in the bank sector. Product data scientists are expected to build a fraud detecting system after analyzing large numbers of transactions.
- SaaS: The recent and trending projects in machine learning is natural language processing (NLP) to provide smarter chatbots.
Product data scientists should acquire the following skills:
- Software Development Basics: you don’t have to be full-time software development or full-stack engineer. But as a product data scientist, you will be working firmly with software engineers. Understanding software developer language is another skillset, if and only if there is a register language for them. You will have to familiar with some console, like agile development, version control, software architectures at a high level.
- Data Pipelines: As a product data scientist, managing data pipelines and database is a big part of your job. Familiar with database language such as PHP, MySQL, etc.
What are the relevant tools you need today to launch your career as a data scientist?
There are many tools you need to launch your career as a data scientist. The list is endless… it depends on how guru you want to become. But, I will limit you to those you will use to find a high-paying job, which is majorly used in Data Science and Machine Learning. However, python or R programming language is an easier language for data science and machine learning career. We also have less common language like Julia or MATLAB but I would recommend python or R.
Aside from employability, do you even consider ease of learning? Let it stick to memory that python programming language is a universal language that can be used for offline and web software development. Also, Python is the most popular language among data scientists. It’s easy to learn.
The following tools are recommended for your learning and they all fall under the Python Stack
- Python – a programming language
- Jupyter Notebook – lightweight IDE
- NumPy – library for numeric computations
- Pandas – library for data management
- Scikit-Learn – library for general –purpose Machine Learning
- Keras – library for neural networks and deep learning
- Matplotlib and Seaborn – libraries for data visualization
What is the best to learn Data Science and Machine Learning for a busy person?
As a busy person, there won’t be time for you to start learning from what is python or what’s data science. However, there is no chance of digging into all maths and theory afresh, which you don’t need.
I’ve two approached for easy learning but one is easier than one. As a busy person/professional, “Top-down” is the best approach while the second approach, “bottom-up” is not very practical for working professionals seeking to a career transition. You will lose motivation along the way because it long and tedious.
The top-down Approach
I recommend the “Top-down” approach because your priority will be to see machine learning or data science project from start to finish. You will start with tutorials instead of lectures. The tutorial will teach you how to do something in a possible way. However, if you follow the tutorial step by step, you will be able to see the entire data science task from start to finish. This is the best way for learning because when you start seeing gigantic pictures, you will know how it fixes together.
How would you solidify your skills in order to become a Data scientist?
After you complete the tutorial, then you apply what you learned to a new dataset. This will help you solidify your skills and begin expanding your knowledge.
For instance, you’re trying some training and testing process on a new dataset, you encounter an error, you google it, upon that you will be discovering some new things. Maybe the dataset is different from the one used in the tutorial, maybe the dataset has different rows and columns, or empty space which is affecting your model to work as you desire. By searching online for possible solutions, you come across new thing and you dig further into the topic to complement what you already know.