Course detail
Data analysis, statistics, visualization and practical workflows for decision-making.
13th round and summer intake
Online classes are live and recorded. In-person learners can choose regular, extension or weekend attendance when available.
Analyze datasets
Create useful charts
Communicate insights clearly
Course experience
Each monthly part should combine instructor-led lessons, resources, checklists, practice work and evaluation gates before learners move on.
Outline highlights
Career value
Data Science is the practice of collecting, cleaning, analyzing, visualizing and explaining data so people and organizations can make better decisions.
The course connects statistics, Python, spreadsheets, visualization and project-based reporting. Learners build the habit of asking clear questions, checking data quality and communicating insights responsibly.
It is valuable for students, analysts, business owners and professionals who want to understand what data says before making decisions.
Transforms messy information into clear insight and practical recommendations.
Builds skills in data cleaning, analysis, charts, dashboards and evidence-based communication.
Works well with many fields: business, finance, education, health, marketing, agriculture and public service.
Creates a strong foundation for machine learning and AI careers.
ዳታ ሳይንስ ብዙ ጥሬ መረጃን በመሰብሰብ፣ በማጽዳት፣ በመተንተን እና በቻርት/ሪፖርት በማቅረብ ጠቃሚ ግንዛቤ የምናወጣበት መስክ ነው።
የዳታ ሳይንስ ባለሙያ ልክ እንደ መርማሪ በመረጃ ውስጥ የተደበቁ ቅጦችን፣ ግንኙነቶችን እና እድሎችን ያገኛል።
ትምህርቱ Python, statistics, data cleaning, visualization እና dashboard/reporting በተግባር ያካትታል።
ውሳኔን በስሜት ሳይሆን በመረጃ ላይ እንዲመሰረት ያግዛል።
በቢዝነስ፣ ትምህርት፣ ጤና፣ ማርኬቲንግ እና ፋይናንስ ዘርፎች ተግባራዊ ነው።
ለማሽን ለርኒንግ እና AI ጠንካራ መነሻ ይሰጣል።
በዙሪያችን ያለው ዓለም በመረጃ የተሞላ ነው፤ የሽያጭ መረጃ፣ የተማሪ ውጤት፣ የጤና መረጃ፣ የማህበራዊ ሚዲያ ባህሪ፣ የትራፊክ ፍሰት እና የደንበኛ ግብይት ሁሉ ዳታ ነው።
ጥሬ ዳታ ብቻውን ጥቅም አይሰጥም። መረጃው ሲሰበሰብ፣ ሲጸዳ፣ ሲተነተን እና በግልጽ ቻርት/ሪፖርት ሲቀርብ ነው ለድርጅት እውነተኛ ውሳኔ የሚረዳው።
የዳታ ሳይንስ ሂደት ችግሩን መረዳት፣ መረጃ መሰብሰብ፣ መረጃ ማጽዳት፣ መረጃን መመርመር፣ ሞዴል መገንባት፣ ውጤት መገምገም እና ለሰዎች በቀላሉ ማብራራት ያካትታል።
ተማሪዎች Python, SQL, Excel, Jupyter Notebook, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn እና dashboard/reporting tools በተግባር ይጠቀማሉ።
የደንበኞች ባህሪ መተንተን፣ የሽያጭ እና የገቢ ትንበያ፣ የsurvey data ማጽዳት፣ የተማሪዎች ውጤት መከታተል፣ የmarketing campaign ውጤት መመዘን እና interactive dashboard መስራት የሚሰሩ ፕሮጀክቶች ናቸው።
የMiT ዳታ ሳይንስ ትምህርት ተማሪዎች ዳታን ለማየት ብቻ ሳይሆን ከዳታው የሚነገር ታሪክ ለመፍጠር እና ለmanager, client ወይም team በሚገባ ለማቅረብ ያስተምራል።
ዳታ ሳይንስ በባንክ፣ ትምህርት፣ ጤና፣ ማርኬቲንግ፣ መንግስት፣ NGO, retail እና technology companies ውስጥ ተፈላጊ እየሆነ ነው።
ይህ ኮርስ Data Analyst, Reporting Officer, Business Intelligence Assistant, Monitoring and Evaluation Data Assistant እና junior Data Scientist ወደሚሉ መንገዶች ያዘጋጃል።
Learn from practitioners who ship production software, campaigns and creative work — then guide your evaluations in the LMS.
Python & Data Science
Python & Data Science Instructor
Teaches Python foundations through data analysis, visualization and practical scripts.
Python & Data Science
Python & Data Science Instructor
Supports learners in Pandas, statistics and decision-ready data projects.
Resources are organized by term, monthly part, week and lesson. Full Stack access opens one part at a time after payment and instructor evaluation.
Unlock after payment or instructor evaluation.
Unlock after payment or instructor evaluation.
Best for students who want structured lab access, instructor support and consistent weekday practice.
Designed for learners who need evening sessions three days per week after work or daytime study.
A practical option for working learners and university students who need weekend attendance.
Live virtual classes are recorded so students can review lessons, recap missed points and continue studying after class.
Available for courses longer than three months when tuition is paid in full.
Available when one student registers for two or three courses.
Special support for students who did not pass university entrance and are not eligible for remedial placement.
For online Full Stack enrollment, one eligible family member can receive tuition waived under the family offer.
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