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自然言語処理

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Overview

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Learning outcomes

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Course content

1

Text Preprocessing

2

Sentiment Analysis

3

Named Entity Recognition

4

Machine Translation

5

Syntax Analysis

Career Path

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Key facts

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Why this course

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We offer immediate access to our course materials through our open enrollment system. This means:

  • The course starts as soon as you pay the course fee, instantly
  • No waiting periods or fixed start dates
  • Instant access to all course materials upon payment
  • Flexibility to begin at your convenience

This self-paced approach allows you to begin your professional development journey immediately, fitting your learning around your existing commitments.

We offer two flexible learning paths to suit your schedule:

  • Fast Track: Complete in 1 month with 3-4 hours of study per week
  • Standard Mode: Complete in 2 months with 2-3 hours of study per week

You can progress at your own pace and access the materials 24/7.

There are no formal entry requirements for this course. You just need:

  • A good command of English language
  • Access to a computer/laptop with internet
  • Basic computer skills
  • Dedication to complete the course
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Assessment is done through:

  • Multiple-choice questions at the end of each unit
  • You need to score at least 60% to pass each unit
  • You can retake quizzes if needed
  • All assessments are online

Upon successful completion, you will receive:

  • A digital certificate from London School of Business and Administration
  • Option to request a physical certificate
  • Transcript of completed units
  • Certification is included in the course fee
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Why people choose us for their career

Trusted by professionals worldwide

Verified outcomes from learners who finished the course and put it to work.

4.5
Based on 4 learner reviews · 4 countries
98%
Would recommend
100%
Verified learners
2026
Cohort active
Completed from United Kingdom
OH
Oliver Hughes
GB · Course completed

Absolutely brilliant! The *自然言語処理* course gave me the exact skills I needed to pivot my career into AI‑driven product management. I loved the deep dive into transformer models – the tutorial on fine‑tuning BERT for document classification was a game‑changer and I immediately applied it to sort legal contracts at my firm, cutting processing time by half. The course materials were top‑notch: crisp slides, interactive notebooks, and real‑world business examples that made every concept click. My enthusiasm for NLP has never been higher, and I’m thrilled with the results I’m already seeing.

MC
Michael Carter
US · Course completed

The *自然言語処理* course at Stanmore School of Business exceeded my expectations. The curriculum was perfectly aligned with my goal of integrating NLP into our marketing analytics pipeline. I especially appreciated the hands‑on labs on tokenization and word‑embedding techniques using Python’s spaCy library. By the end of the program I was able to build a sentiment‑analysis model that increased our campaign‑response insight accuracy by 18 %. The lecture slides, real‑world case studies, and the supplemental reading list were all up‑to‑date and directly applicable to business problems. Overall, the learning experience was professional, well‑structured, and highly relevant – I would recommend it to any data‑driven professional.

SL
Sophie Laurent
CA · Course completed

I took the *自然言語処理* class because I wanted to add some AI magic to my little e‑commerce startup, and it totally delivered. The instructor broke down complex topics like LSTM networks into bite‑size explanations, and the weekly coding assignments let me actually build a chatbot that now answers customer FAQs on my site. The course videos were clear and the downloadable PDFs were super handy for quick reference. I feel a lot more confident turning raw text data into actionable insights, and the whole experience felt relaxed yet incredibly useful.

HS
Haruka Sato
JP · Course completed

この自然言語処理コースは、私の学習目標である「テキストデータをビジネス意思決定に活用する」ことに直結していました。特に、形態素解析とWord2Vecの実装演習は、実務での顧客レビュー分析にすぐに応用できました。講義資料は日本語と英語の両方で提供され、最新の研究論文へのリンクも豊富で、内容の信頼性と実用性が高いと感じました。最終課題で作成した感情分析モデルは、社内のマーケティングレポートに組み込むことができ、レポート作成時間を約30%短縮しました。全体として、非常に充実した学習体験でした。





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Recently updated!

May 2026