Data Analysis and Machine Learning: Python + GPT 3.5 & GPT 4

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Md Shahriar,Intelli Analytica

8:56:19

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1 - Setting Up Your Analysis Environment

1 - Install Python and Jupyter Notebook.html

1 - Mac.pdf

1 - Windows.pdf

2 - Setting up ChatGPT and GPT 4.mp4

02:20

3 - Download Practice datasets.html

3 - Practice-datasets.zip

3 - Practice-datasets-for-GPT-4.zip

2 - Data Analysis and Its Workflow

4 - Data Analysis and Its Characteristics.mp4

07:11

5 - Complete data analysis workflow.mp4

02:55

3 - Statistical Analysis and Its Workflow

6 - Statistical Analysis and Its Characteristics.mp4

08:09

7 - Confidence level significance level and Pvalue.mp4

05:05

8 - Complete hypothesis testing workflow.mp4

07:40

4 - Machine Learning and Its Workflow

9 - Machine Learning and Its Characteristics.mp4

03:35

10 - Complete Machine Learning Workflow.mp4

02:39

5 - Python Programming Basics Level 1

11 - Your First Python Code.mp4

04:36

12 - Variables and naming conventions.mp4

09:05

13 - Data types integers float strings boolean.mp4

07:22

14 - Type conversion and casting.mp4

09:49

15 - Arithmetic operators.mp4

06:44

16 - Comparison operators.mp4

07:36

17 - Logical operators and or not.mp4

07:06

6 - Python Programming Basics Level 2

18 - Lists creation indexing slicing modifying.mp4

15:59

19 - Sets unique elements operations.mp4

07:51

20 - Dictionaries keyvalue pairs methods.mp4

09:23

21 - Conditional statements if elif else.mp4

07:04

22 - Logical expressions in conditions.mp4

09:57

23 - Looping structures for loops while loops.mp4

09:12

24 - Defining Creating and Calling functions.mp4

05:11

7 - Python GPT 35 Learn Data Cleaning

25 - Loading dataset.mp4

07:06

26 - Handling missing values.mp4

12:43

27 - Deal with inconsistent data.mp4

11:17

28 - Dealing with missidentified data types.mp4

07:43

29 - Dealing with duplicated data.mp4

04:22

8 - Python GPT 35 Learn Data Manipulation

30 - Sorting and arranging dataset.mp4

05:17

31 - Filter data based on conditions.mp4

10:34

32 - Merging or adding variables.mp4

03:47

33 - Concatenating extra data.mp4

03:47

9 - Python GPT 35 Learn Data Preprocessing

34 - Feature engineering.mp4

16:29

35 - Extracting day months year.mp4

04:24

36 - Feature encoding.mp4

05:31

37 - Creating dummy variables.mp4

07:14

38 - Data normalizing.mp4

12:19

39 - Splitting data.mp4

06:53

10 - Python GPT 35 Learn Regressor Machine Learning

40 - Linear regression ML model.mp4

18:18

41 - Decision Tree regression ML model.mp4

08:08

42 - Random Forest regression ML model.mp4

08:04

43 - Support Vector regression ML model.mp4

06:26

11 - Python GPT 35 Learn Classification Machine Learning

44 - Logistic Regression ML model.mp4

21:44

45 - Decision Tree classification ML model.mp4

13:12

46 - Random Forest classification ML model.mp4

11:50

47 - K Nearest Neighbours classification ML model.mp4

20:31

12 - Python GPT 35 Learn Clustering Machine Learning

48 - KMeans Clustering ML model.mp4

22:05

13 - Python GPT 4 Rapid Data Cleaning

49 - Getting Started with GPT4 Data Analyst.mp4

02:29

50 - Identify missing values.mp4

04:58

51 - Impute missing values.mp4

06:01

52 - Exploring data types.mp4

04:30

53 - Finding inconsistent values.mp4

03:18

54 - Dropping inconsistent values.mp4

03:23

55 - Dealing with duplicates.mp4

07:03

14 - Python GPT 4 Instant Data Manipulation

56 - Sorting dataset.mp4

04:17

57 - Filtering datasets.mp4

04:21

58 - Inner joining method.mp4

05:59

59 - Other joining methods.mp4

03:30

60 - Boxcox transformation.mp4

06:36

61 - Feature binning.mp4

04:16

62 - Feature encoding.mp4

03:35

63 - Creating dummy variables.mp4

03:16

15 - Python GPT 4 Fasttrack Data Analysis

64 - Nominal data analysis.mp4

04:43

65 - Descriptive analysis.mp4

06:19

66 - Group by data analysis.mp4

03:46

67 - Crosstabulation analysis.mp4

09:05

68 - Correlation analysis.mp4

05:14

16 - Python GPT 4 Quick Hypothesis Testing

69 - Oneway ANOVA analysis.mp4

08:17

70 - Pearson correlation analysis.mp4

05:04

71 - Regression analysis.mp4

06:46

17 - Python GPT 4 Build Machine Learning Models

72 - Feature scaling and preprocessing.mp4

04:34

73 - Splitting data into train and test sets.mp4

03:12

74 - Build and evaluate ML models.mp4

05:34

Description

Hands-on Data Analysis and Machine Learning in Python + GPT 3.5. Apply GPT-4 to Analyze and Develop ML Models Smoothly.

What You'll Learn?

Learn to proficiently use Python for various machine learning tasks, including data cleaning, manipulation, preprocessing, and model development.
Gain expertise in building and implementing supervised machine learning models: Regressions, Classifications, Random Forest, Decision Tree, SVM, and KNN, etc.
Acquire skills in unsupervised machine learning techniques, including KMeans for effective cluster analysis and pattern recognition.
Develop the ability to measure and evaluate the accuracy and performance of machine learning models, enabling decisions on model selection and optimization.
Apply acquired knowledge to real-world scenarios, solving diverse machine learning challenges and developing solutions.
Learn to efficiently prepare and clean datasets using GPT-4, including handling missing data, outliers, and data type conversions.
Master the use of GPT-4 for advanced data manipulation tasks, such as merging datasets, creating pivot tables, and applying conditional logic.
Develop skills to utilize GPT-4 for creating and interpreting a variety of data visualizations, such as histograms, scatter plots, and line graphs.
Learn to apply GPT-4 for predictive analytics, including random forest regressor and other machine learning models.
Acquire the ability to automate repetitive data analysis tasks using GPT-4, enhancing efficiency and productivity.

Who is this for?

Python Enthusiasts enhance their programming with AI

Data Science aspirants looking for hands-on course

Complete Beginners wants to learn machine learning easiest way

Anyone wants to simplify and fasten data analysis workflow with ChatGPT

What You Need to Know?

No coding Experience is Needed.

Laptop/Desktop and Internet

More details

Description
Accelerate your journey to mastering data analysis and machine learning with our dynamic course: "Data Analysis and Machine Learning: Python + GPT 3.5 & GPT 4". Immerse yourself in a comprehensive curriculum that seamlessly integrates essential tools such as Pandas, Numpy, Seaborn, Scikit-learn, Python, and the innovative capabilities of ChatGPT.
Embark on an immersive learning experience designed to guide you through every facet of the machine-learning process. From data cleaning and manipulation to preprocessing and model development, you'll traverse each stage with precision and confidence.
Dive deep into hands-on tutorials where you'll gain proficiency in crafting supervised models, including but not limited to Linear Regression, Logistic Regression, Random Forests, Decision Trees, SVM, XGBoost, and KNN. Explore the realm of unsupervised models with techniques like KMeans and DBSCAN for cluster analysis.
Our strategic course structure ensures swift comprehension of complex concepts, empowering you to navigate through machine learning tasks effortlessly. Engage in practical exercises that not only solidify theoretical foundations but also enhance your practical skills in model building.
Measure the accuracy and performance of your models with precision, enabling you to make informed decisions and select the most suitable models for your specific use case. Beyond analysis, learn to create compelling data visualizations and automate repetitive tasks, significantly boosting your productivity.
By the course's conclusion, you'll possess a robust foundation in leveraging GPT-4 for data analysis, equipped with practical skills ready to be applied in real-world scenarios. Whether you're a novice eager to explore machine learning or a seasoned professional seeking to expand your skill set, our course caters to all levels of expertise.
Join us on this transformative learning journey, where efficiency meets excellence, and emerge with the confidence to tackle real-world data analysis and machine learning challenges head-on with python and GPT. Fast-track your path to becoming a proficient data analysis and machine learning practitioner with our dynamic and comprehensive course.
Who this course is for:
Python Enthusiasts enhance their programming with AI
Data Science aspirants looking for hands-on course
Complete Beginners wants to learn machine learning easiest way
Anyone wants to simplify and fasten data analysis workflow with ChatGPT

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Introducing Shahriar: Accomplished Data Analyst and Passionate InstructorWelcome to the dynamic world of data analytics, where every byte of information holds the key to unlocking insights and shaping informed decisions. Meet Shahriar, a seasoned freelancer and a dedicated data enthusiast, who is now poised to share his wealth of knowledge and expertise as an esteemed Instructor at Udemy.With a rich tapestry of experiences spanning over three prolific years in the field, Shahriar has made an indelible mark as a Data Analyst extraordinaire. Over the course of his illustrious career, he has successfully spearheaded and completed an impressive portfolio of more than 300 projects, transcending geographical boundaries and leaving a trail of satisfied clients worldwide.Proficient in an array of cutting-edge tools and languages including Python, R, Excel, and SPSS, Shahriar's prowess extends across a spectrum of domains within the data realm. His unparalleled skills encompass data analysis, machine learning, data manipulation, data visualization, and applied statistics, to name just a few. His holistic approach to problem-solving ensures that every project is meticulously analyzed, curated, and executed to perfection, delivering results that are not just insightful but also actionable.However, what truly sets Shahriar apart is his unwavering passion for data. To him, data is more than just numbers and figures; it's a story waiting to be told. As an avid storyteller, he seamlessly weaves narratives from complex datasets, transforming raw information into compelling insights that resonate with both experts and novices. Shahriar's ability to make data relatable and engaging underscores his dedication to demystifying the world of data analytics.As he steps into his new role as an Instructor at Udemy, Shahriar is committed to sharing his wealth of knowledge with a global audience. His teaching philosophy is rooted in clarity, accessibility, and practicality. Whether you're a budding data enthusiast taking your first steps or a seasoned professional seeking to refine your skills, Shahriar's meticulously crafted courses are designed to empower and elevate your data prowess.In conclusion, Shahriar's journey from a passionate data hobbyist to a prolific freelancer and now an esteemed Udemy Instructor is a testament to his unwavering dedication, insatiable curiosity, and relentless pursuit of excellence in the realm of data analytics. Embark on this transformative learning journey with Shahriar and unravel the mysteries of data in a way that only a true storyteller can unveil. The world of data analytics awaits, and Shahriar is your guiding light.

Intelli Analytica

Instructor's Courses

Greetings from IntelliAnalytica! I'm excited to guide you on this exploration of artificial intelligence (AI) and data analysis. I have a strong interest in data science and artificial intelligence, and I can use my years of experience and knowledge to help you become an expert at utilizing cutting-edge technology to extract insightful information from data.I have worked with data analysis tools and AI algorithms extensively as a seasoned professional in the area, obtaining practical knowledge in turning raw data into usable intelligence. My mission is to equip students like you with the know-how and abilities required to succeed in the data-driven world of today.Come discover the limitless potential of artificial intelligence-powered data analysis with us at IntelliAnalytica. Together, let's unleash the power of data and set out on an exciting educational journey. I'll see you in class.

Udemy

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