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9 must-have skills you need to become a Data Scientist

9 must-have skills you need to become a Data Scientist

Data Science is creating tremendous opportunities for certified and skilled data analysts and data scientists as it is growing rapidly with emerging technologies around the world. It launches many innovative things and equipment that simplify the efforts of humans and rectify human errors effectively. A career in Data Science becomes the best thing for freshers and those who want to transform their careers into a data analytics platform. But there are numerous top-notch skills to be improved and they are the key points to prove as best analyst or data scientist in big companies. We have collected them from industrialists and given here the must-have Data Science skills required for a candidate to enter into the data science domain.

  1. Python as highest consideration

The in-depth Knowledge of Python programming language along with mathematical and statistical skills is considered the most important to become a data scientist. Most of the survey reveals that Python is growing in popularity as it is user-friendly for developers, testers, scriptwriters, data scientists, and analysts. The learning of the Python programming language brings a promising start in the data science platform as it simplifies complicated work like algorithm creation and implementation. Other programming languages like R, SAS, and SQL are added advantage to perform as per the client’s expectations.

  1. Strong in Python Library usage

Python programming language has tons of libraries to implement where it is repeatedly called functions and mundane coding. The library usage quickens the development and implementation of the project and most of the Python Libraries are easy to use, interpret, and implement. Python libraries can provide useful insights to perform the data correlation and data integration effectively. There are some popular frameworks and libraries in Python that work efficiently for machine learning processing, deep learning concepts, and data analytics. Some of them are TensorFlow, PyTorch, Theano, and Keras and they are used mostly in the process of solving the complexity of advanced problems in data science.

  1. Understanding of GPU hardware and CUDA

Data Science processing depends on the hardware as it is used for implementing to solve most complicated deep learning models, machine learning algorithms, and artificial intelligence works that include neural network, NLP (Natural Language Processing), Image processing, and pattern works. The hardware knowledge is important to install and implement powerful machines that contain highly configured CPUs to perform these scientific computations. GPU (Graphical Processing Unit) along with CUDA (Compute Unified Device Architecture) is used to perform and accelerate scientific computations and data analytics effectively with speed and accuracy. The deep knowledge in GPU and CUDA along with hands-on practice helps the candidate to get a job easily in big firms for working as data scientists.

  1. In-depth understanding of algorithms

Numerous algorithms such as logical regression, linear regression, decision trees, SVM algorithms, Naïve Bayes, KNN algorithm, K-means algorithm, and random forest algorithm, dimensionality reduction algorithms, and gradient boosting algorithm and AdaBoosting algorithm are popularly utilized in data science process and implemented in various projects. 71% of data scientists are implementing these algorithms for performing various scientific computations and numerical calculations.

  1. An acquaintance in Cloud Service Providers

Big companies are adapting to cloud practice from on-premise solutions for easy access, cost-effectiveness, and data security. A situation like Pandemic makes employees work from home and it relies on Cloud Computing for providing uninterrupted solutions to users. The knowledge in Cloud Service providers is the need of the hour and nearly 70% of companies using AWS, 20% of companies using Azure and many companies are using other small providers as per their investments.

  1. Proficiency in Visualization tools

Data Visualization is the main part of the data science process as it displays the data in an understandable format to clients as well as industry leaders. There are some frequently used tools in the market such as Tableau, PowerBI, and MSBI, and so on. The learning of visualization tools helps the candidate to perform a data visualization process that becomes useful for decision-making purposes.

  1. Knowledge of Github usage

Data Scientists are utilizing this Github Platform to collaborate and contribute their projects for the benefit of beginners and enterprise project managers. There is a wide range of projects available in Github and many of them are available as open-source. Finding a suitable project that can be useful for developing projects is helpful for the data scientist to fasten the development and deployment.

  1. Well-versed with available IDEs

IDE (Integrated Development Environment) is used to write, debug, and implement codes, and sometimes data scientists require to develop a code or some for their projects. These IDEs are used to complete the debugging process, resource management, and another related process. Notebook, PyCharm, and RStudio are widely used by data scientists around the world and the knowledge of them is useful for beginners to perform the same.

  1. Hadoop Expertise

Big Data Analytics is the recent trend as the world generates trillions of data every day through applications and website usage. These large amounts of data to be structured for the decision-making process and it offer a cost-effective solution by using the tools like Hadoop. Therewith, the expertise in Hadoop is considered a must-have skill, and learning them will be helpful for the students to sustain strongly in data science platform.

End Note

Demand for data scientists and data analysts are growing every day and you can check them in job portals. All the job descriptions contain the above skills and gaining expertise in these areas helps attain the job easily in big companies. The certification along with hands-on exposure is required in all areas and top institutes in Chennai provide them to bridge the knowledge gap of global industries.

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RPA (Robotic Process Automation) is an automated rule-based business processes to do efficient execution of deploying robots with cost-effective development. RPA reduces the human involvement in the process of automating workflow with the help of robots or software applications. There are three main terms you as a beginner need to understand:  Robotic, Process, and Automation.

Robotic: Entities that are mimic human actions.

Process: Systematic process steps for executing a meaningful activity.

Automation: Automatic action that is done by a robot without any human intervention.

These three terms together make mimicking the human actions by performing the sequence of steps and brings an effective activity without human interaction is known as Robotic Process Automation.RPA requires some basic skills for learning it with capable of understanding the business requirements and convert them into Automated Process using some RPA tools like Blue Prism, UiPath, Automated Anywhere, and so on.

Thankfully, learning RPA need not any in-depth knowledge on coding, because all the RPA tools have kind of unique mechanism to learn it quickly and deeply. However, you need to develop your logical and analytical skills and strong future is guaranteed for the one who is practicing on it.

Here, the list of skills given below which are required for learning RPA and we are sure it will help you to equip for the better software development and outshine your skills in developing RPA applications.

  • Basic Knowledge in VB and .Net framework as most of the RPA tools are developed in it.
  • Understanding of VBA Macros, Excel, and its implementation
  • Fundamental of writing and integrating Python scripts with RPA toolset
  • Basic understanding about building components like Auto-ML, NLP, and AI integrations such as Microsoft Luis or IBM Watson
  • Basics of document capture technologies such as ABBYY
  • Fundamentals of Business Process Modelling or UML (Unified Modelling Language)
  • Knowledge on Business Exceptions Handling
  • Understanding of Data Parsing with the use of XML, JSON
  • Practice with APIs in workflow development

Other than these technical skills, there are some more logical skills required to enhance in the following fields:

  • Systematic thinking
  • High level programming mindset
  • Active learning with update awareness
  • Basic mathematical concepts
  • Science and applied mathematics knowledge
  • Good judgmental and decision-making ability
  • Expert level in communication to deliver your ideas
  • Ability to solve complex problems in an easy way
  • Basic knowledge about technology design
  • Persistence in the field in any kind of situation

These basic skills will help you to learn RPA technology effectively and apply them in real time on the project development at the time of learning itself. Investing your time on developing the above said skills bring more opportunities on RPA development projects with more productivity and result-oriented outputs to the enterprises.

We can understand the requirement of RPA developers through the wide range of applications that are found in the market. Many reputed companies like Amazon, Google, and Facebook are continually in the making of RPA projects to meet the global needs of automating process like data analytics, transactions, and some other functions.

RPA Developers generally have three basic roles such as Process Designer, Automation Architect, and Production Manager. Some of the required skills for RPA developers are listed below for the on-demand roles of top companies:

Role: Process Designer

Requires Skills:

  1. Strong Analytical and Problem-Solving skills
  2. Basic experience in one or more RPA tools (Blue Prism, UI Path, and Automation Anywhere)
  3. Minimum one year of experience in coding or scripting in any programming languages, SQL databases, and application development
  4. Practice in Process Analysis, Design, and Implementation even as internship level
  5. Ability to prioritize and handle multiple portfolios
  6. Basic knowledge in Lean Six Sigma process methodologies

Role: Automation Architect

Required Skills:

  1. Better to have certifications in any of the field such as ITIL, TOGAF, CoBIT, PMP, Lean Six Sigma, and Prince2
  2. Ability to narrate technical specification documentation for required RPA projects
  3. Ability to develop complete technical architecture for any kind of RPA projects with extensible and scalable features
  4. Adequate hands-on experience in any of the following RPA tools such as Automation Anywhere, Blue Prism, UiPath, Open Span, Redwood, and WorkFusion, etc.
  5. Strong knowledge in any of the programming languages like C/C++, Python, VB Script, Java, Ruby, JavaScript, and .Net
  6. Basic knowledge in handling tools like NICE, Nuance, Enterprise Systems SAP, OCR Tools, Oracle, Custom Apps, PeopleSoft, ITSM Tools Service Now, Jira, BMC Remedy, etc.
  7. Fundamentals of Automation platforms, frameworks, and tools, etc.

Role: Production Manager

Required Skills:

  1. Minimum 2 to 3 years of experience in RPA Project development and implementations
  2. Strong knowledge in Architecture and Delivery experience
  3. More hands-on experience with real time projects using RPA tools
  4. Well-built knowledge in innovativeness and ability to integrate creative technologies
  5. Minimum 5 years of technical experience in IT industry
  6. Minimum 0-3 years of experience in Robotic Process Automation using any RPA tools and in-depth knowledge in it
  7. Aware of related RPA technologies and its version up to date

End Note:

Learning RPA and its tools will be complicated without developing the required skills for producing the unique software application development in the market. Because many companies are involved today in the process of developing the efficient RPA applications and they required developers with strong skills on the mentioned field along with the certification. Get valuable certification course in the best RPA Training Institute in Chennai at SLA Institute to acquire and equip the adequate skills to perform from day one in reputed companies.

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The post 9 must-have skills you need to become a Data Scientist appeared first on Best Software Training Institute in Chennai – 100% Placement.



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