<prompt> Hlalosa phapang lipakeng tsa rasaense oa data le moenjiniere oa ho ithuta ka mochini.nan  <response>: Instruction in English: Explain the difference between a data scientist and a machine learning engineer. . Response in English: Data Scientist and Machine Learning Engineer are both key players in the field of computer science and artificial intelligence. Though the roles might sound very similar, there are some fundamental differences between both:1. Scope of work: Data Scientist is primarily responsible for analyzing and interpreting complex data, and using this analysis to help businesses in making strategic decisions. On the other hand, Machine Learning Engineer is responsible for building and implementing machine learning algorithms to improve a companys processes and products.2. Practical skills: A Data Scientists skills usually include a strong foundation in mathematics, statistics, computer science, and data visualization. They work closely with data to identify trends, and must be able to use analytics tools very effectively. On the other hand, Machine Learning Engineers must have strong programming skills so they can code algorithms, conduct data modelling and create datasets. They need to be well-versed in machine learning algorithms and must be able to apply them in practice.3. Interdisciplinary approach:Data Scientists often must be able to work across different departments, and need to communicate their findings effectively to members of the company who have little or no technical background. Machine Learning Engineers primarily work within the IT, data and engineering departments.To summarize, a Data Scientist is responsible for designing and implementing models that extract meaningful insights from data, while Machine Learning Engineers build, implement, and maintain machine learning systems in the companys products and processes. . Response in Sesotho: Data Scientist le Machine Learning Engineer ka bobeli ke libapali tsa bohlokoa lefapheng la mahlale a khomphutha le bohlale ba maiketsetso. Leha mesebetsi e kanna ea utloahala e tsoana haholo, ho na le liphapang tsa mantlha lipakeng tsa bobeli: 1. Sebaka sa mosebetsi: Data Scientist ke eena ea ikarabellang bakeng sa ho sekaseka le ho hlalosa lintlha tse rarahaneng, le ho sebelisa tlhahlobo ena ho thusa likhoebo ho etsa liqeto tsa maano. Ka lehlakoreng le leng, Moenjineri oa ho Ithuta oa Mochini o ikarabella ho aha le ho kenya tšebetsong li-algorithms tsa ho ithuta ka mochini ho ntlafatsa litsebetso le lihlahisoa tsa khamphani. 2. Tsebo ea ho sebetsa: Tsebo ea A Data Scientist hangata e kenyelletsa motheo o tiileng oa lipalo, lipalo, saense ea khomphutha, le pono ea data. Ba sebetsa haufi-ufi le data ho tseba mekhoa, me ba tlameha ho sebelisa lisebelisoa tsa analytics ka katleho haholo. Ka lehlakoreng le leng, Baenjiniere ba ho Ithuta ba Mechini ba tlameha ho ba le litsebo tse matla tsa ho etsa mananeo e le hore ba tsebe ho etsa li-algorithms, ho etsa mohlala oa data le ho etsa li-database. Ba hloka ho ba le tsebo e ntle ea li-algorithms tsa ho ithuta ka mochini mme ba tsebe ho li sebelisa tsebetsong. 3. Mokhoa o fapaneng oa mekhoa e fapaneng: Hangata boramahlale ba data ba tlameha ho sebetsa mafapheng a fapaneng, me ba hloka ho buisana ka katleho le litho tsa khamphani tse nang le tsebo e fokolang ea tekheniki kapa tse se nang letho. Baenjiniere ba ho Ithuta ba Mechini ba sebetsa haholo-holo ka hara lefapha la IT, la data le la boenjiniere. Ho akaretsa, Data Scientist e ikarabella bakeng sa ho rala le ho kenya tsebetsong mefuta e ntšang lintlha tse utloahalang ho tsoa ho data, ha Baenjiniere ba ho Ithuta ba Mochini ba haha, ba kenya tsebetsong le ho boloka mekhoa ea ho ithuta ka mochine lihlahisoa le mekhoa ea khamphani. 