<prompt> Hlalosa mehato ea ho ba rasaense ea data.nan  <response>: Instruction in English: Describe the steps to become a data scientist. . Response in English: Becoming a data scientist typically involves the following steps:1. Pursue a strong educational background: A degree in a quantitative field such as statistics, computer science, mathematics, or engineering is often required. However, many data scientists also have backgrounds in natural or social sciences, with a strong emphasis on quantitative coursework.2. Develop technical skills: Familiarize yourself with programming languages such as Python or R, and learn to use data manipulation, analysis, and visualization tools such as SQL, Excel, and Tableau. You should also have a good understanding of statistics, machine learning, and data mining techniques.3. Gain real-world experience: Look for internships, co-ops, or other opportunities to work on data science projects, either in an academic or business context. This will help you gain practical knowledge and experience, and will be a valuable addition to your resume.4. Keep learning: Data science is a continually evolving field, so its important to stay abreast of new developments and continue to expand your skills. Take courses, attend workshops, and keep reading about new techniques, tools, and concepts.5. Build a professional network: Join data science communities or organizations, both online and in-person. Attend meetups, conferences, and workshops to meet others in the field, share knowledge and experiences, and make professional connections.6. Apply for data science positions: With your educational background, technical skills, and experience, youll be well-prepared to start applying for data scientist roles. Remember to tailor your resume and cover letter to each job and highlight your most relevant experience and skills. . Response in Sesotho: Ho ba rasaense oa data hangata ho kenyelletsa mehato e latelang: 1. Ho phehella maemo a matla a thuto: Ho hlokahala lengolo la thuto ea lipalo-palo joalo ka lipalo, saense ea khomphutha, lipalo, kapa boenjiniere hangata lia hlokahala. Leha ho le joalo, bo-rasaense ba bangata ba data le bona ba na le semelo sa mahlale a tlhaho kapa a kahisano, ba hatelletse haholo lithutong tsa bongata. 2. Hlaolela litsebo tsa botekgeniki: Itloaetse lipuo tsa mananeo tse kang Python kapa R, me u ithute ho sebelisa lisebelisoa tsa ho fetola, ho hlahloba le ho bona litšoantšo tse kang SQL, Excel, le Tableau. U lokela hape ho ba le kutloisiso e ntle ea lipalo-palo, ho ithuta ka mochini, le mekhoa ea ho rafa data. 3. Fumana boiphihlelo ba lefatše la nete: Batla li-internship, li-co-ops, kapa menyetla e meng ea ho sebetsa mererong ea mahlale a data, ebang ke maemong a thuto kapa khoebo. Sena se tla u thusa ho fumana tsebo e sebetsang le boiphihlelo, me e tla ba tlatsetso ea bohlokoa ho qalelle ea hau. 4. Tsoela pele ho ithuta: Saense ea data e lula e fetoha, kahoo ho bohlokoa ho lula u tseba ntlafalo e ncha le ho tsoela pele ho holisa tsebo ea hau. Nka lithuto, u ee lithupelong, me u lule u bala ka mekhoa e mecha, lisebelisoa le mehopolo. 5. Theha marang-rang a setsebi: Eba karolo ea sechaba sa mahlale a data kapa mekhatlo, ka marang-rang le ho motho ka mong. E-ea likopanong, likopanong, le lithupelong ho kopana le ba bang tšimong, ho arolelana tsebo le liphihlelo, le ho etsa likamano tsa litsebi. 6. Etsa kopo ea maemo a saense ea data: Ka semelo sa hau sa thuto, tsebo ea tekheniki, le boiphihlelo, u tla be u itokisitse hantle ho qala ho etsa kopo ea likarolo tsa bo-ramahlale ba data. Hopola ho hlophisa qalelle ea hau le lengolo la sekoahelo bakeng sa mosebetsi o mong le o mong le ho totobatsa boiphihlelo le boiphihlelo ba hau bo loketseng. 