Dataconomy

JULY 24, 2023

Tools like Tableau, Matplotlib, Seaborn, or Power BI can be incredibly helpful. Learn relevant tools Familiarize yourself with data science tools and platforms, such as Tableau for data visualization, or Hadoop for big data processing. This is where data visualization comes in.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

Mlearning.ai

DECEMBER 4, 2023

Leverage Tools for Enhanced Data Analysis Evolve beyond basic tools like Excel by exploring advanced platforms such as Power BI, Tableau, or even Python for more intricate analyses. Power BI and Tableau can create interactive dashboards that users can easily play with data.

Power BI 52

Power BI Data Analysis Data Analysis Tableau 52

Pickl AI

JANUARY 9, 2025

Expertise in tools like Power BI, SQL, and Python is crucial. Expertise in programs like Microsoft Excel, SQL , and business intelligence (BI) tools like Power BI or Tableau allows analysts to process and visualise data efficiently. AI and automation play a central role in the evolving role.

Power BI 52

Power BI Machine Learning Machine Learning Tableau 52

Mlearning.ai

MARCH 15, 2023

Experience with visualization tools like; Tableau and Power BI. High proficiency in visualization tools like; Tableau, Google Studio, and Power BI. Knowledge of big data platforms like; Hadoop and Apache Spark. Basic programming knowledge in R or Python.

Data Science 52

Data Science Analytics Analytics Data Analyst 52

Mlearning.ai

FEBRUARY 22, 2023

This could involve using tools like Tableau or Power BI to create visualizations and dashboards. This could involve using tools like Apache Spark or Apache Flink to perform data transformations, analytics, and machine learning. Secure the data : Data security is a critical part of any big data architecture blueprint.

Big Data 52

Big Data Big Data Power BI Hadoop 52

ODSC - Open Data Science

APRIL 6, 2023

One set of tools that are becoming more important in our data-driven world is BI tools. Think of Tableau, Power BI, and QlikView. This allows for it to be integrated with many different tools and technologies to improve data management and analysis workflows.

SQL 98

SQL Data Scientist Database Data Science 98

ODSC - Open Data Science

APRIL 3, 2023

Data Analytics Platforms: Tableau, Power BI, Looker, Alteryx, Google Analytics, SPSS, SAP, Pandas. The most common trend shouldn’t come as a surprise, as the most in-demand data analytics platforms revolve around reporting, such as Tableau, Power BI, Looker, Alteryx, Google Analytics, SPSS, and SAP.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

Pickl AI

JANUARY 31, 2023

Along with Tableau, the curriculum also provides supervised and unsupervised learning opportunities. In effect, the Certified Data Science professional programme includes topics like Data Analysis and Visualisation, ML models, Predictive models , NLP etc.

Data Science 52

Data Science Machine Learning Machine Learning Data Scientist 52

Mlearning.ai

FEBRUARY 9, 2023

Users like to see the data directly and manipulate the data using published programs like Tableau, Power BI, or whatever URL site you select (it could be a google sheet or a github repository transformed into a github page). WARNING that some code snippets MIGHT not work ? It was very easy to setup!

Power BI 52

Power BI Data Analysis Data Analysis Tableau 52

Pickl AI

JULY 10, 2024

Machine Learning (ML) is a subset of AI that involves using statistical techniques to enable machines to improve their performance on tasks through experience. On the other hand, ML focuses specifically on developing algorithms that allow machines to learn and make predictions or decisions based on data.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

Pickl AI

DECEMBER 4, 2024

The rise of advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML) , and Big Data analytics is reshaping industries and creating new opportunities for Data Scientists. Learn to use tools like Tableau, Power BI, or Matplotlib to create compelling visual representations of data.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

phData

APRIL 5, 2024

By harnessing the advancements of LLMs, users can now extract key information buried within large documents without any code or ML knowledge required. Before diving into the technology that powers Document AI, let’s go over some of the utility that extracting your information offers. Why is Document AI Important?

AI 52

AI AI Natural Language Processing Tableau 52

Pickl AI

APRIL 28, 2023

Here is the tabular representation of the same: Technical Skills Non-technical Skills Programming Languages: Python, SQL, R Good written and oral communication Data Analysis: Pandas, Matplotlib, Numpy, Seaborn Ability to work in a team ML Algorithms: Regression Classification, Decision Trees, Regression Analysis Problem-solving capability Big Data: (..)

Data Scientist 52

Data Scientist Data Science Hypothesis Testing Decision Trees 52

Mlearning.ai

JULY 11, 2023

Moreover, tools like Power BI and Tableau can produce remarkable results. For instance, feature engineering and exploratory data analysis (EDA) often require the use of visualization libraries like Matplotlib and Seaborn. These tools can be employed later on to automate tasks and create a smoother workflow.

Data Science 40

Data Science Exploratory Data Analysis Azure Power BI 40

phData

DECEMBER 12, 2023

Step 2: Analyze the Data Once you have centralized your data, use a business intelligence tool like Sigma Computing , Power BI , Tableau , or another to craft analytics dashboards. It also leads to more company-wide collaboration and cuts unnecessary organizational expenses.

Data Warehouse 52

Data Warehouse Machine Learning Machine Learning Tableau 52

AWS Machine Learning Blog

MAY 30, 2024

Principal ML Prototyping Solutions Architect at AWS Tamil Jayakumar is a Sr. Principal Enterprise Architect at CBRE Chakra Nagarajan is a Sr. Prototyping Engineer at AWS Shane Madigan is a Sr. Engagement Manager at AWS Maran Chandrasekaran is a Sr. Solutions Architect at AWS VB Bakre is an Account Manager at AWS

AWS 128

AWS SQL Database AI 128

Pickl AI

FEBRUARY 19, 2025

Here are some of the most essential elements of Data Science: Machine Learning (ML): Helps computers learn from data and make predictions without direct programming; powers recommendation systems like those on Netflix or Amazon. Tableau and Power BI : Visualisation tools that create interactive dashboards and reports.

Data Science 52

Data Science Analytics Analytics Machine Learning 52

ODSC - Open Data Science

JANUARY 7, 2025

As MLOps become more relevant to ML demand for strong software architecture skills will increase aswell. Machine Learning As machine learning is one of the most notable disciplines under data science, most employers are looking to build a team to work on ML fundamentals like algorithms, automation, and so on.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Pickl AI

SEPTEMBER 12, 2023

Besides, there are free ML courses and ChatGPT courses that will help you keep up with the trends in the industry.

Data Science 52

Data Science Data Analyst Machine Learning Machine Learning 52

Mlearning.ai

AUGUST 10, 2023

I can make html/javascript webpages, code in javascript/html, I used python flask, streamlite, deployed google script coded figures to http endpoints, used numerous visualization/app programs like Tableau/Power BI/Looker, and made many API endpoints.

Power BI 52

Power BI Database Tableau Python 52

Pickl AI

MARCH 7, 2025

The Power of Machine Learning and AI in Data Science Machine Learning (ML) and AI are integral components of Data Science that enable systems to learn from data without explicit programming. Example: Netflix uses ML to recommend shows based on viewing history. Example: Netflix uses ML to recommend shows based on viewing history.

Data Science 52

Data Science Machine Learning Machine Learning Data Scientist 52

ODSC - Open Data Science

MARCH 12, 2025

20212024: Interest declined as deep learning and pre-trained models took over, automating many tasks previously handled by classical ML techniques. This shift suggests that while traditional ML is still relevant, its role is now more supportive rather than cutting-edge.

Data Science 52

Data Science Machine Learning Machine Learning Data Engineering 52