名無しのコスメ好きさん on LIPS 「Data Analytics Syllabus ..」

埋め込み

<iframe class="lips-embed"  src="https://lipscosme.com/embed/posts/7783705" width="100%" height="245" style="border: none;" referrerpolicy="strict-origin-when-cross-origin" loading="lazy" title="LIPSの投稿"></iframe><script src="https://lipscosme.com/embed/embed.js" async></script>

埋め込みコードをコピー

この埋込みコードを使用することで、当社の利用規約及びプライバシーポリシーに同意するものとします。

投稿・コメントの報告

投稿日：2025年08月02日

名無しのコスメ好きさん1週間前
Thank you for sharing such a detailed and well-structured Data Analytics syllabus. It’s really helpful for beginners to understand the complete learning path—from fundamentals like data collection and cleaning to advanced topics like predictive analytics and machine learning. The inclusion of tools like SQL, Python, Tableau, and Power BI makes it very practical and industry-relevant. This kind of roadmap is great for anyone planning to build a strong career in data analytics. Also, for those who are interested in expanding their skills beyond analytics and exploring digital growth opportunities, I found this resource useful: https://www.pdmti.in/online-digital-marketing-course Thanks again for the informative post!

Data Analytics Syllabus Module 1: Introduction to Data Analytics What is data analytics? Role of a data analyst Types of analytics: Descriptive, Diagnostic, Predictive, Prescriptive Data-driven decision making Module 2: Data Collection & Data Sources Types of data: Structured vs. unstructured Data sources: Databases, APIs, web scraping, surveys Data warehousing and data lakes Introduction to ETL (Extract, Transform, Load) processes Module 3: Data Cleaning & Preprocessing Importance of clean data Handling missing or inconsistent data Data transformation and normalization Tools: Excel, Python (Pandas), R Module 4: Exploratory Data Analysis (EDA) Descriptive statistics: Mean, median, mode, standard deviation Data profiling Identifying trends and patterns Visualization tools: Matplotlib, Seaborn, Tableau, Power BI Module 5: Data Visualization & Communication Best practices for visual storytelling Creating reports and dashboards Tools: Tableau, Power BI, Google Data Studio Module 6: Statistical Analysis Probability and distributions Hypothesis testing Correlation vs. causation Linear and logistic regression Module 7: SQL for Data Analytics Basics of databases Writing SQL queries Joins, filters, and aggregations Data manipulation and extraction Basic syntax and data structures Data analysis libraries (Pandas, NumPy, Matplotlib) Reading, analysis, and visualization of data Introduction to scripting and automation Module 9: Predictive Analytics (Advanced/Optional) Introduction to machine learning Supervised and unsupervised learning Model construction and assessment Algorithms: Decision trees, clustering, regression https://www.sevenmentor.com/data-analytics-courses-in-pune.php https://www.iteducationcentre.com/data-analytics-courses-in-pune.php

名無しのコスメ好きさん

@supreme_lips_uwsi

0フォロー
0フォロワー
19いいね

ピックアップ記事

LIPSタイアップ | PR

春の朝を心地いい時間に！ご機嫌スイッチをオンにする3つのTIPS

春の新生活、朝からちょっぴりお疲れモードになっていませんか？バタバタしがちな朝を、ほんの少しだけ「ごきげんな時間」に変える3つのヒントをご紹介。時短なのに頼れる高機能アイテムでゆとりをつくって、思わず鏡を見たくなる"爆ビジュ"アイテムで気分をぐっと底上げ。PR MEDIHEAL、パーフェクトワン、アパガード

記事を読む