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人工知能プロジェクトのデータ分析認定(上級) (Advanced)

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Overview

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Learning outcomes

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Course content

1

データ前処理とクレンジング

2

特徴量エンジニアリング

3

探索的データ分析

4

統計的モデリング

5

機械学習アルゴリズム選定

6

深層学習モデル構築

7

モデル評価指標

8

ハイパーパラメータ最適化

9

データ可視化技法

10

ビジネスインパクト評価

11

データパイプライン設計

12

スケーラブルaiシステム

13

倫理と公平性評価

14

Aiプロジェクト管理

15

成果物ドキュメンテーション

16

パフォーマンスモニタリング

17

継続的学習とモデル更新

18

クラウドaiサービス活用

19

データガバナンスとコンプライアンス

20

プレゼンテーションとステークホルダーコミュニケーション

Career Path

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Key facts

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Why this course

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  • Instant access to all course materials upon payment
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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
ST
Sarah Thompson
GB · Course completed

I took this course to upskill for a new role in AI analytics, and it delivered. The practical sessions on feature engineering for large‑scale datasets were spot‑on – I used the techniques straight away on a client project and saw a 15% boost in model accuracy. The video lessons were clear, and the supplementary reading was up‑to‑date with the latest research. While the pace was a bit fast at times, the overall experience was very positive and I feel ready to tackle senior‑level AI projects.

MC
Michael Carter
US · Course completed

The advanced AI project data analysis certification exceeded my expectations. The curriculum directly aligned with my goal to lead a predictive‑modeling team, and the hands‑on labs on deep‑learning pipelines gave me the confidence to design end‑to‑end solutions. I especially appreciated the detailed case studies on time‑series forecasting, which I now apply to our company's sales forecasts. The course materials were current, well‑structured, and the instructor feedback was prompt and insightful. Overall, a professional and highly rewarding learning experience.

AP
Ananya Patel
IN · Course completed

Wow! This course was exactly what I needed to transition from a data analyst to an AI specialist. The modules on neural‑network optimization were explained with real‑world examples, and I could immediately apply the hyper‑parameter tuning tricks in my own Kaggle submissions – I moved from a bronze to a gold rank within weeks! The course platform was user‑friendly, and the community forum helped me solve doubts quickly. I'm thrilled with the knowledge I gained and highly recommend it to anyone serious about AI project data analysis.

ZD
Zanele Dlamini
ZA · Course completed

The certification offered a deep dive into advanced data analysis techniques for AI projects. I particularly valued the segment on model interpretability, which equipped me with SHAP and LIME tools that I now use to explain model decisions to stakeholders. The course material was comprehensive, with up‑to‑date references and clear slide decks. Although some sections could have included more local case studies, the overall learning journey was thorough and has already improved my performance at work.





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May 2026