<prompt> Hlalosa litsebo tsa tekheniki tse hlokahalang bakeng sa karolo ea Data Scientist.nan  <response>: Instruction in English: Specify technical skills that are required for Data Scientist role. . Response in English: A data scientist needs a combination of technical skills to excel in their role. Some of the key technical skills required for a data scientist include:1. Statistical Analysis: A strong understanding of statistical techniques and concepts like probability distributions, hypothesis testing, and regression analysis.2. Programming: Proficiency in at least one programming language, usually Python or R, to perform data wrangling, analysis and visualization.3. Machine Learning: Knowledge of various machine learning techniques such as supervised and unsupervised learning, decision trees, and neural networks, and the ability to apply them to real-world problems.4. Data Manipulation and Analysis: Familiarity with tools and libraries to manipulate large datasets, such as NumPy, Pandas, and SQL.5. Data Visualization: Ability to present complex data in an easy-to-understand visual format, with the use of tools such as Matplotlib, Seaborn, and Tableau.6. Big Data Technologies: Familiarity with big data technologies such as Hadoop, Spark, and NoSQL databases to work with large datasets.7. Cloud Computing: Understanding of cloud computing platforms such as Azure, AWS, or GCP to store, process, and analyze large amounts of data.In summary, a data scientist needs strong statistical and mathematical knowledge, programming and data manipulation skills, knowledge of machine learning algorithms and data visualization techniques, and proficiency in big data technologies and cloud computing platforms. . Response in Sesotho: Setsebi sa data se hloka motsoako oa litsebo tsa tekheniki ho ipabola karolong ea bona. Tse ling tsa litsebo tsa bohlokoa tsa tekheniki tse hlokehang bakeng sa rasaense oa data li kenyelletsa: 1. Tlhahlobo ea Lipalopalo: Kutloisiso e matla ea mekhoa ea lipalo-palo le likhopolo tse kang kabo ea menyetla, tlhahlobo ea maikutlo, le tlhahlobo ea ho khutlela morao. 2. Lenaneo: Tsebo ea bonyane puo e le ngoe ea lenaneo, hangata Python kapa R, ho etsa likhohlano tsa data, tlhahlobo le pono. 3. Ho Ithuta ka Mechini: Tsebo ea mekhoa e fapaneng ea ho ithuta ka mochine e kang ho ithuta ho hlokomeloa le ho sa laoloe, lifate tsa liqeto, le marang-rang a methapo ea kutlo, le bokhoni ba ho li sebelisa mathateng a sebele a lefatse. 4. Tšebeliso le Tlhahlobo ea Boitsebiso: Ho tloaelana le lisebelisoa le lilaebrari ho laola li-dataset tse kholo, tse kang NumPy, Pandas, le SQL. 5. Ponahalo ea Boitsebiso: Bokhoni ba ho hlahisa lintlha tse rarahaneng ka mokhoa o bonolo oa pono o utloisisoang habonolo, ka tšebeliso ea lisebelisoa tse kang Matplotlib, Seaborn, le Tableau. 6. Big Data Technologies: Ho tloaelana le litheknoloji tse kholo tsa data tse kang Hadoop, Spark, le NoSQL databases ho sebetsa le li-dataset tse kholo. 7. Cloud Computing: Kutloisiso ea li-platform tsa cloud computing tse kang Azure, AWS, kapa GCP ho boloka, ho sebetsa le ho hlahloba lintlha tse ngata. Ka bokhutšoanyane, rasaense oa data o hloka tsebo e matla ea lipalo-palo le lipalo, tsebo ea ho hlophisa le ho laola lintlha, tsebo ea li-algorithms tsa ho ithuta ka mochine le mekhoa ea ho bona lintlha, le tsebo ea mahlale a maholo a data le li-platform tsa cloud computing. 