Data Science Dojo

JULY 3, 2024

Tools like Tableau, Power BI, and Python libraries such as Matplotlib and Seaborn are commonly taught. Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Pickl AI

MAY 29, 2024

Proficiency with tools like Tableau , Matplotlib , and ggplot2 helps create charts, graphs, and dashboards that effectively communicate insights to stakeholders. This knowledge allows the design of experiments, hypothesis testing, and the derivation of conclusions from data.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Pickl AI

JULY 25, 2023

Statistical Analysis: Hypothesis testing, probability, regression analysis, etc. Machine Learning: Supervised and unsupervised learning techniques, deep learning, etc. Data Visualization: Matplotlib, Seaborn, Tableau, etc. TensorFlow, Scikit-learn, Pandas, NumPy, Jupyter, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

SEPTEMBER 23, 2024

AI, particularly Machine Learning and Deep Learning uses these insights to develop intelligent models that can predict outcomes, automate processes, and adapt to new information. Deep Learning: Advanced neural networks drive Deep Learning , allowing AI to process vast amounts of data and recognise complex patterns.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

Pickl AI

AUGUST 9, 2024

Students should learn about data wrangling and the importance of data quality. Statistical Analysis Introducing statistical methods and techniques for analysing data, including hypothesis testing, regression analysis, and descriptive statistics. Students should learn about neural networks and their architecture.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

APRIL 26, 2024

Yes, I am proficient in data visualisation tools such as Tableau, Power BI, and Matplotlib in Python, which I use to create interactive and insightful visualisations for data analysis. Are there any areas in data analytics where you want to improve or learn more? Lifetime access to updated learning materials.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52