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    Home»Featured»Here’s What You Should Know About Data Science Syllabus
    Featured

    Here’s What You Should Know About Data Science Syllabus

    DESI-STORIESBy DESI-STORIESNovember 13, 2020No Comments5 Mins Read
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    Data Science Syllabus2 1
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    Did you know that in 2019, 2.9 million data science jobs were created? As per statistics, 11.5 million new data science jobs will be available by 2026. Due to the ever increasing volume of data and the shortage of data scientists, more and more professionals are looking to switch their careers to the field of data science. Learning online while simultaneously working, is one how one can pick up this new skill and uplight their career. But before you do so, make sure of what you are going to learn, and who you are going to learn it from. You can check out the data science syllabus from different platforms and compare them to find the best fit for you! 

    Data Scientist Skills

    Data Scientists have exciting jobs, they help organizations to solve problems by combining computer science, modeling, statistics, analytics, and math skills—along with sound business sense. They uncover the answers to major questions that enable organizations to take data driven decisions. 

    Data Science Syllabus1 1

    Source: Ekimetrics.com

    Majorly, Data Scientist Skills are categorized into hard skills and soft skills. Hard skills are the abilities that can be acquired and enhanced through practice, repetition, and education whereas soft skills are a combination of people skills, social skills, communication skills that one possesses. The soft skills, while being very important, are relatively easier to learn. Here are 6 hard skills that every data scientists should know about:

    1. Programming Skills to extract data and perform analysis on platforms like Python, R and SQL.
    2. Math & Statistics to understand the data, find patterns and implement algorithms. 
    3. Machine Learning to create algorithms that have the ability to automatically learn and improve from experience without being explicitly programmed.
    4. Data Wrangling to clean, format and organize the data before implementing any algorithms. 
    5. Data Visualization & Communication to present findings/ observations to the stakeholders. These need to be created in a way that even the non technical team members are able to understand it easily.

    All of these skills are covered in Springbaord’s Data Science Syllabus with some additional benefits for learners.

    Data Science Career Track with Online Classroom

    Springbaord’s Data Science Syllabus is made for students with a prior background in statistics and programming. This course will help with the following things:

    1. Build job ready skills – Master foundations of data science and choose your focus area like advanced machine learning, natural language processing, or deep learning.
    2. Develop a professional portfolio – Complete 14 real-life projects, including two industry-worthy capstone projects to showcase your skills to employers.
    3. Launch your dream career – Make yourself hireable with personalized career coaching and 1:1 mentorship from industry experts.

    What is the syllabus for Data Science?

    Springboard starts by introducing the python data science stack. Here we cover concepts that help you use Python and its standard libraries. Students also get introduced to the tools and libraries used in the worlds of data science and engineering, build visualizations with Matplotlib and Seaborn and write clear and readable code in Python using the PEP8 standard! 

    Once this section is done, we pick up on data wrangling & data story sections where the students can practice the concepts that they have learnt so far. By joining in, you can get the opportunity to explore a dataset,perform analyses & present a storyline to a panel.

    The next important segment of data science is learning statistical inference and parameter estimation. An important step, learners use hypothesis testing to determine if a phenomenon is statistically significant. We also teach how to build A/B split tests and perform exploratory data analysis as a part of our Data Science Syllabus.

    Data Science Syllabus2 1

    Source: SecurityRoundtable.com

    We then cover Machine learning and its importance in data science. Our learners work on libraries like scikit-learn, pandas, seaborn to implement supervised and unsupervised algorithms & evaluate ML systems. To hone your data scientist skills better, Springboard provides the option of choosing a dataset of learners preference for the capstone project. On joining us, you will be able to choose real life data from any industry of your preference for your data science project.

    To help learners choose the right data science career path, Springboard also provides career assistance during placements. Let’s see how the career path is, after learning data sciences. 

    Data Science Career Path

    Data Science career trends and opportunities and ever-growing and they are here to stay. Even though this has a pretty stable path, you can face challenges while changing career paths in the beginning. Springboard ensures that our learners don’t face any such challenge and can land a job easily after completing the certification.

    Data Science Syllabus3 1

    Source: theladders.com

    A career services team provides a job guarantee to every student. Right from getting your resume correct to updating your LinkedIn, a personal coach helps with search strategy & networking principles that will help you land your first job! Our learners even get assistance with salary negotiations. 

    To get a jump start, check out the data science syllabus covered by Springboard and assess if this is the right course for you! Join like minded professionals on a new expedition to learn data science!

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