Can I become a Data Scientist?

Comprehensive description of Knowledge Areas and Skills set one needs to become a Data Scientist!

In today’s Covid-19 impacted world, businesses are slowing down and so is job demand and employment avenues. However one job which is still in demand and in fact growing is for Data Scientist and Data Analysts and hence many of you wonder what it takes to become a Data Scientist. Here we describe the Knowledge Path to become a successful Data Scientist so that you can understand and explore it and if it interests you , you may even get into it to grow quickly in your career.


Ambeone Can I become a Data Scientist?

Following are the Five Main Knowledge and Skills Area you need to master:

First Area: Knowledge of Statistics Techniques.

  • Aggregate functions like Mean, Medium & Mode
  • Probability Theory
  • Normal & Gaussian Distribution
  • Confidence Intervals
  • Hypothesis Testing
  • Intro to Linear Regression

Second Area :Data Interpretation, Business Intelligence & Business Insights

  • Foundations of Statistical Modelling & Statistical Inference
  • Sampling Strategies & Experimental Designs
  • Understanding Sources of Data
  • Generating Key Performance Indicators (KPI’s)
  • Implementing Business Intelligence & Business Analytics Solutions
  • Interpreting Data Trends & Generating Business Insights
  • Making Business Decisions based on Data Insights

Third Area: Big Data Analytics with R & Python

  • Analyze large and complex datasets with ease.
  • Clean untidy datasets and merge datasets.
  • Advanced data exploration and data mining.
  • Advanced data visualizations and graphs.
  • Using data mining and Visualizations to structure frame business problems and potential solutions.

Fourth Area: Machine Learning & Predictive Modeling

  • Linear & Logistic Regression
  • Classification – Decision Tree & Random Forest
  • K-Means Cluster Analysis
  • Bayesian ML : A/B Testing
  • Support Vector Machines
  • Recommender Systems
  • Principal Component Analysis
  • Natural Language Processing
  • Recommender Systems
  • Using these techniques and models for different business challenges

Fifth Area: Artificial Intelligence & Deep Learning

  • Neural Networks
  • Perceptron & Activation Functions
  • Cost Functions & Gradient Descent Back propagation
  • TensorFlows & Theano Implementation
  • Convolution Neural Networks
  • Recurrent Neural Networks
  • Artificial Intelligence: Reinforcement Learning
  • Vibrational Autoencoders
  • Generative Adversarial Networks (GANS)
  • Using these techniques to create solutions and models for business needs and innovation

The above areas describe comprehensively the most important and in-demand knowledge areas and skills needed as Data Scientists.You may learn them at your pace and in different combinations and get Data Science related jobs of different levels. Important thing to note is that you do not have to master all levels at same time and can began small and step-wise. Later you can also  specialize in one area/technique  and become a domain expert in that depending on your interest and capabilities.

However having good foundation in Statistics is essential to progress in this field so you do need to get your concepts cleared in that.

After that as they say ‘Sky is the Limit’ and  you can grow exponentially in the field . You will be able to help organisations grow , analyse world situations through data , minimize uncertainties & risks  and even design  innovative AI solutions to help business and human welfare. If you wish to check your suitability for this field , you may take our Data Science Aptitude Test. You may also check out our courses to know the Data Science Series path you can take to  make a career as a Data Scientist and you can also talk to our Consultant in a One one One session to check if these programs  are relevant for your aspirations and career goals.



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