What You'll Learn
- Understand data science foundations, applications, and the path to becoming a data scientist.
- Analyze data using Python programming with variables, loops, functions, and OOP.
- Apply statistics and probability with distributions, hypothesis testing, and inference in Python.
- Perform data cleaning, transformation, and EDA using pandas and NumPy.
- Visualize data with Python using bar charts, histograms, scatterplots, heatmaps, and box plots.
- Build regression, classification, and clustering models with scikit-learn and evaluate performance.
- Master advanced ML techniques like cross-validation, feature engineering, regularization, and hyperparameter tuning.
- Implement ensemble learning methods such as Random Forest, AdaBoost, CatBoost, LightGBM, and XGBoost.
- Explore deep learning with neural networks and TensorFlow, from preprocessing to model evaluation.
- Gain hands-on experience through real-life projects and assessments to build a strong portfolio.
- Acquire Excel, SQL, Python, Power BI, and ChatGPT skills to prepare for a data analyst career.
- Learn data analysis foundations with statistics, hypothesis testing, and machine learning.
- Use Excel for data cleaning, manipulation, formulas, functions, graphs, and charts.
- Apply Excel advanced tools like pivot tables, Analysis ToolPak, and interactive dashboards.
- Understand RDBMS fundamentals including keys, data types, and relational models.
- Work with MySQL for table manipulation, constraints, indices, filtering, and joins.
- Learn Python basics including variables, data types, lists, dictionaries, loops, and functions.
- Master Python for data cleaning, manipulation, preprocessing, and transformation.
- Use Python for visualization, exploratory analysis, statistics, and ML modeling.
- Utilize ChatGPT for data manipulation, merging, pivot tables, and conditional logic.
- Apply ChatGPT for predictive analytics with Random Forest and ML models.
- Learn Power BI for data manipulation, analysis, and dashboard insights.
- Create professional, story-driven dashboards in Power BI with impactful visuals.
- Complete 30+ assignments, 120+ coding exercises, and 10 quizzes with 100+ questions.
- Accomplish 4 capstone projects: bank churn analysis, sports analytics, HR data management and website performance analysis.
- Accomplish 7 AI projects: Image Captioning, Chatbot, Voice Assistant, Text to Image, Video Summarizer, Language Translator and Data Analyst AI
Requirements
- Access to computer and internet
- Basic computer literacy
- No coding experience required
- Dedication, patience and perseverance
Who This Course is For
- Everyone!
Your Instructor
Analytix AI
Unleashing the Power of Data with AI for Informed Insights.
4.5 Instructor Rating
744 Reviews
16,301 Students
13 Courses
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