Learn Data Science, Deep Learning, Machine Learning, NLP & R
Learn Data Science, Deep Learning, Machine Learning, NLP & R | Udemy Coupon EDLearn Data Science, Deep Learning, Machine Learning, Natural Language Processing, R and Python Language with libraries. Get Udemy Coupon Code
What you'll learn
- Mathematics and Statistics behind Machine Learning
- Mathematics and Statistics behind Deep Learning
- Mathematics and Statistics behind Artificial Intelligence
- Python Programming Language from Scratch
- Python with it's Libraries
- Learn Numpy, Pandas, Matplotlib, Scikit-Learn
- Learn Natural Language Processing
- Learn R Language
- Learn Tokenization in Natural Language Processing
- Learn Implementation of R Packages and Libraries on Different Data Sets
- Learn Implementation of Python Libraries on Different Data Sets
- Algorithms and Models of Machine Learning
- Algorithms and Models of Deep Learning
- Learn Data Science
- k-Nearest Neighbors, Naive Bayes etc
- Supervised and Unsupervised Learning
Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills.
What Does a Data Scientist Do?
In the past decade, data scientists have become necessary assets and are present in almost all organizations. These professionals are well-rounded, data-driven individuals with high-level technical skills who are capable of building complex quantitative algorithms to organize and synthesize large amounts of information used to answer questions and drive strategy in their organization. This is coupled with the experience in communication and leadership needed to deliver tangible results to various stakeholders across an organization or business.
Data scientists need to be curious and result-oriented, with exceptional industry-specific knowledge and communication skills that allow them to explain highly technical results to their non-technical counterparts. They possess a strong quantitative background in statistics and linear algebra as well as programming knowledge with focuses in data warehousing, mining, and modeling to build and analyze algorithms.
Glassdoor ranked data scientist as the #1 Best Job in America in 2018 for the third year in a row. 4 As increasing amounts of data become more accessible, large tech companies are no longer the only ones in need of data scientists. The growing demand for data science professionals across industries, big and small, is being challenged by a shortage of qualified candidates available to fill the open positions.
The need for data scientists shows no sign of slowing down in the coming years. LinkedIn listed data scientist as one of the most promising jobs in 2017 and 2018, along with multiple data-science-related skills as the most in-demand by companies.
Where Do You Fit in Data Science?
Data is everywhere and expansive. A variety of terms related to mining, cleaning, analyzing, and interpreting data are often used interchangeably, but they can actually involve different skill sets and complexity of data.
Data scientists examine which questions need answering and where to find the related data. They have business acumen and analytical skills as well as the ability to mine, clean, and present data. Businesses use data scientists to source, manage, and analyze large amounts of unstructured data. Results are then synthesized and communicated to key stakeholders to drive strategic decision-making in the organization.