Description
Data Analytics, Data Science, & Machine Learning – All in 1. This comprehensive course will put you on the path to becoming a data scientist from beginner to advanced. This integrated program covers essential skills and practical tools in three key areas: data analytics, data science, and machine learning. It is designed with a step-by-step, cumulative structure to transform theoretical knowledge into practical capabilities and ultimately job readiness. In an era where the AI revolution and tools like ChatGPT, Stable Diffusion, and AI assistants for coding and analysis have transformed the job market, this course focuses on creating real, tangible solutions to real-world problems. The main goal is to provide deep, practical knowledge with an emphasis on action, critical thinking, and the creation of practical projects so that participants, regardless of their previous experience, can succeed in the dynamic data space and prepare themselves for the demands of today’s job market.
What you will learn
- Data Science and Python Basics:
- Learning how to think like a data scientist, not just coding.
- Python basics: variables, loops, conditionals, functions, data structures.
- Data Cleaning, Data Manipulation, and EDA (Exploratory Data Analysis) with Pandas and NumPy.
- Using ChatGPT for advanced ML data analysis and predictions.
- Proficiency in Excel, SQL, Python and Power BI:
- Excel: Manipulate data, perform calculations, and create visualizations.
- SQL: Querying and manipulating relational databases.
- Python: Data analysis and visualization, workflow automation, and advanced dashboard creation.
- Power BI: Connect to multiple data sources, clean and transform data, and design interactive dashboards.
- Exploratory Data Analysis (EDA):
- Understand the shape, distributions, and nature of raw data.
- Visualization of relationships using Matplotlib and Seaborn.
- Develop strong data insight and hypothesis-building skills.
- Probability, statistics, and mathematics for data science:
- Probability Distributions and Descriptive Statistics.
- Inferential Statistics: Confidence intervals, Hypothesis Testing.
- Linear Algebra and Calculus required for ML.
- Machine Learning (ML) and Feature Engineering:
- Complete ML workflow: preprocessing, training, validation, and testing.
- Algorithms: Logistic Regression, Decision Trees, Random Forests, and Ensemble Methods.
- Model evaluation: Accuracy, Precision, Recall, F1-score, ROC-AUC.
- Feature Engineering: Encoding categorical variables, Scaling/Normalizing, and Building Pipelines.
- Hyperparameter Tuning.
- Deep Learning and Generative AI:
- Neural Networks with TensorFlow: Activation Functions, Backpropagation, Optimizers.
- Prompt Engineering and the use of generative AI tools to generate text, images, code, and video.
- Real-world applications of AI: Chatbots, translators, voice assistants, and video summaries.
- Projects and practical training:
- More than 30 assignments, 120 coding exercises, and 10 tests.
- Capstone projects: Banking data analysis, sports data analysis, fraud detection, and ML deployment.
- 7 complete generative AI projects: including building Image Captioning AI, Chatbot with LLaMA2/Gemma, and AI Data Analyst.
This course is suitable for people who:
- Everyone!
- Individuals looking to acquire technical and professional skills for data analyst and data scientist roles.
- Those who want to become experts in Excel, SQL, Python, Power BI, TensorFlow, and other related tools.
- Those interested in strengthening analytical and critical thinking abilities.
- People who want to build a strong portfolio of real-world projects to present in interviews or freelancing opportunities.
- Those who intend to qualify for entry-level to mid-level roles in data science, ML engineering, or analytics.
Course details
- Publisher : Udemy
- Teacher : Analytix AI
- Language: English
- Level : All Levels
- Lectures : 492
- Duration : 65 hours and 51 minutes
Course syllabus
Prerequisites for the Data Analytics Data Science & Machine Learning – All in 1 course
- Access to computer and internet
- Basic computer literacy
- No coding experience required
- Dedication, patience and perseverance
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: English
Quality: 1080p
The 2026/7 version has the duration decreased by 13 minutes compared to 2025/9.
Download link
File(s) password: www.downloadly.ir
File size
33.97 GB
