Any insights on the course Cloud Computing and Big Data by Prof. Sahu for MS CS Machine Learning track?
In terms of how hard and easy is it, and can I combine it with hard subjects like ML, or Algo? Or should I take it with lighter subjects?
As an alternative, is Big Data Analytics a good course as well, in terms of being helpful in job scenario?
Big 4: IT Audit Associate: 56.5k
Big 4: Promotion: 62k
No Name Company: Data Reporting Analyst: 70k
Big Tech: Analyst: 140k
I had a bachelors and a minor in IT I wanted to stay at big 4 to do data analytics but the team didn’t want me until later in 2020 months so I left to no name company. I figured out exactly what industry I wanted while working at no name. I improved my skills tremendously in python and sql at no name. I started applying to specific companies around last October.
I got the job at the no name company by posting a basic python project on GitHub
In college I worked as a database developer and I had a lot of knowledge on how tables and queries and sql worked.
Funny enough my new company really loved that I had consulting experience from big 4 and honestly I don’t think I would’ve gotten this opportunity if I didn’t come from big 4. I look at most of the other people at my new job and most of them have consulting experience
I guess some advice to give is to just know you’re worth and don’t settle for anything less
Edit: I got into a free bootcamp for data science and analytics and most of the material I knew such as python and sql because I learned it at the no name company but I mostly was in it to understand more of the statistical concepts and data visualizations
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... keep reading on reddit ➡The big data analytics certifications from the Data Science Council of America (DASCA) offer in-depth knowledge related to managing the entire life–cycle of analyzing big data with the help of advanced analytics tools and techniques on usual and most popular big data platforms and software.
DASCA offers two kinds of global certification programs in the field of big data analytics. They are:
- Associate Big Data Analyst (ABDA™) – This is specially meant for aspiring graduate students who have completed majors in business, management, economics, statistics, marketing, or allied disciplines, and who aim to pursue a big data analytics career.
- Senior Big Data Analyst (SBDA™) – This data analytics certification is largely aimed at experienced analytics, research, and marketing professionals whose goal is to either shift into the big data field or for those professional individuals who are already working in the field of big data and wants to grow further in their prospective careers.
Data is the lifeline of Artificial intelligence and Big data analytics. Data is the only driving force in the world today. Most valued asset without which we cannot hope for prosperity in today's crowded markets. If these data are used efficiently, then this data can be conducive to corporate growth. This requires effective integration of data analytics and artificial intelligence.
Integrating big data analysis enables quick, more informed decisions and access to real-time data. It has the potential to be a game-changer in a company's commitment to digital transactions. Many data analysis companies extend to help businesses reach great heights and create new business models. Implementing big data analytics and AI in your existing business model will give you real results and help the organisation to succeed in digital transformation. The purpose of the digital transformation process is to use digital transformation to build or modify consumer experiences, cultures, business processes to meet customer demands and market conditions.
This is where AI comes in. It has the potential to help businesses create a digital product development life cycle. It has the potential to create a digital product development life cycle. Businesses can also use AI-driven Big Data Analytics to get precise information about an individual or various groups of clients. This includes information like on which websites they spend time, what they purchase, and purchasing frequency. Businesses can use this data to make improvements to fulfil customer demands . As a result, to complete their digital transformation, organisations must use data and big data analytics.
Artificial intelligence is building smart machines capable of performing tasks that require human intelligence. You can find the application of artificial intelligence in our daily lives. They are –
- Smart assistants like Alexa and Siri
- Mapping of Diseases and Prediction tools
- Manufacturing and drone robots. – drone robots help to access opportunities in manufacturing for research and practice.
- Optimised, personalised healthcare treatment recommendations
- Spam filters on email
- Social media monitoring tools for false or dangerous content.
- Song or TV recommendation from Netflix or Spotify
Digit
... keep reading on reddit ➡There are literally trillions of dollars on the line here. This isn't just a battle between Melvin/Shitadel vs Retail Investors. We are talking about potentially the largest transfer of wealth in history. There are a lot of shady fucks on both sides of this trying to come out on top when this is all said and done (or along the way). There are just-as-evil-as-Melvin hedge funds and whales that are now long on GME and trying to make a shitload of money, but don't think for a minute that they are looking out for you or your personal interests.
TLDR; It's important to look at things from a 35,000ft view every now and then to truly understand the scale of this thing. Put things into perspective and fucking prep your brain and emotions for what they need to endure to end up on the moon!
None of this is financial advice. Just my personal opinion on this situation.
💎🙌🚀🚀🚀🚀🌕
Estoy por recibirme de contador y estoy interesado en el data science, Big data y data análisis, me falta la parte de informatica pero con ese perfil me puede meter en alguna de esas áreas?
