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データサイエンス上級認定証 (Advanced)

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Overview

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Learning outcomes

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Course content

1

データ前処理と特徴量エンジニアリング

2

探索的データ分析

3

統計的モデリングと推論

4

機械学習アルゴリズムの実装

5

深層学習基礎

6

モデル評価とチューニング

7

時系列分析

8

自然言語処理

9

画像認識とコンピュータビジョン

10

ビッグデータ処理と分散コンピューティング

11

データ可視化とダッシュボード作成

12

倫理とプライバシーの考慮

13

データパイプラインと自動化

14

クラウド上のデータサイエンス

15

強化学習入門

16

因果推論と実験設計

17

統計的学習理論

18

データガバナンスと品質管理

19

プロジェクトマネジメント

20

プレゼンテーションとストーリーテリング

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
ST
Sarah Thompson
GB · Course completed

I signed up for the データサイエンス上級認定証 to sharpen my analytics chops, and it delivered. The practical labs on time‑series forecasting helped me build a model for my company's sales data, which is now being used in monthly forecasts. The course material is well‑structured – each chapter builds on the previous one, and the case studies feel very relevant. While the pacing was a bit fast at times, the overall learning experience was solid and I feel ready for more senior data‑science roles.

MC
Michael Carter
US · Course completed

The データサイエンス上級認定証 exceeded my expectations. The curriculum was perfectly aligned with my goal of mastering advanced machine‑learning pipelines. I was able to apply the new techniques on a real‑world project at work, reducing model training time by 30 % thanks to the efficient data‑wrangling modules. The lecture videos were crisp, and the supplemental Jupyter notebooks were up‑to‑date with the latest libraries. Overall, the course gave me the confidence to lead a data‑science team, and I’m extremely satisfied with the results.

ST
Sakura Tanaka
JP · Course completed

Wow! This course was exactly what I needed to move from basic statistics to cutting‑edge AI. The hands‑on sessions with TensorFlow and PyTorch let me create a deep‑learning model for image classification, which I later used in a personal project to detect defects in manufacturing parts. The resources—especially the curated research papers—were top‑notch and kept me up to date with industry trends. I loved the enthusiastic teaching style; it made complex topics feel exciting. I’m thrilled with how much I’ve grown.

ZD
Zanele Dlamini
ZA · Course completed

The データサイエンス上級認定証 provided a detailed and comprehensive pathway to advanced analytics. I appreciated the depth of the modules on feature engineering and model validation, which I applied to a health‑care dataset to improve predictive accuracy from 78 % to 85 %. The course materials were thorough—clear slide decks, well‑commented code, and a rich library of real‑world datasets. The only drawback was that the discussion forums were sometimes quiet, but the instructor’s feedback on assignments was prompt and insightful. Overall, the experience was highly valuable for my career development.





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Recently updated!

May 2026