Get to learn all what it takes to be a skilled Python data analyst, along with insights into real-world examples, by taking this wonderful course in Become a Python Data Analyst. This course has been developed to guide individuals with a basic knowledge on Python to enhance their data analysis skills using the Python libraries and tools, and could be a great way to boost up their candidature to get into or progress within the data analysis, data science, business analysis, business intelligence and web development fields of work.
This e-course will start off by walking you through Anaconda distribution that allows you to access all the popular Python libraries, followed up by a tour on the Jupyter notebook computing platform that is essential for basic python coding purposes. This course will then move you onto explore the NumPy library of the Python programming language that is widely used in numerical and scientific computing activities and the Panda library that allows data analysis using Pytho.
You will get to discover the concepts essential to use Mtplotlib in Python and the Exploratory Data Analysis to apply them in real-world dataset. The SciPy library in Python that is used in statistical computing will also be discussed in-depth through this course, along with attention to the concepts of predictive analysis models and its relationship with machine learning. By the end of this course, you will have a well-grounded knowledge on data analysis using Python to make significant progress within the industry.
Global Edulink offers the most convenient path to gain recognised skills and training that will give you the opportunity to put into practice your knowledge and expertise in an IT or corporate environment. You can study at your own pace at Global Edulink and you will be provided with all the necessary material, tutorials, qualified course instructor, narrated e-learning modules and free resources which include Free CV writing pack, free career support and course demo to make your learning experience more enriching and rewarding.
The course will be directly delivered to you, and you have 12 months access to the online learning platform from the date you joined the course. The course is self-paced and you can complete it in stages, revisiting the lectures at any time.
With this certificate in your resume, you are sure to impress potential employers into hiring you for a number of jobs in the job market. This certificate will also pave way for your career progression by putting you in line to demand for salary increments of job promotions from your employer. Mentioned below are some of the jobs this certificate will help you land, along with the average UK salary per annum according to https://www.payscale.com/career-path-planner,
|Online Training User Manual||00:00:00|
|E Certificate Download Guide||00:00:00|
|Section 1: The Anaconda Distribution and the Jupyter Notebook|
|1.1. The Course Overview||00:00:00|
|1.2. The Anaconda Distribution||00:00:00|
|1.3. Introduction to the Jupyter Notebook||00:00:00|
|1.4. Using the Jupyter Notebook||00:00:00|
|Section 2: Vectorizing Operations With NumPy|
|2.1. NumPy: Python’s Vectorization Solution||00:00:00|
|2.2. NumPy Arrays: Creation, Methods and Attributes||00:00:00|
|2.3. Using NumPy for Simulations||00:00:00|
|Section 3: Pandas: Everyone’s Favorite Data Analysis Library|
|3.1. The Pandas Library||00:00:00|
|3.2. Main Properties, Operations and Manipulations||00:00:00|
|3.3. Answering Simple Questions about a Dataset – Part 1||00:00:00|
|3.4. Answering Simple Questions about a Dataset – Part 2||00:00:00|
|Section 4: Visualization and Exploratory Data Analysis|
|4.1. Basics of Matplotlib||00:00:00|
|4.3. The Object Oriented Interface||00:00:00|
|4.4. Common Customizations||00:00:00|
|4.5. EDA with Seaborn and Pandas||00:00:00|
|4.6. Analysing Variables Individually||00:00:00|
|4.7. Relationships between Variables||00:00:00|
|Section 5: Statistical Computing With Python|
|5.1. SciPy and the Statistics Sub-Package||00:00:00|
|5.2. Alcohol Consumption – Confidence Intervals and Probability Calculations||00:00:00|
|5.3. Hypothesis Testing – Does Alcohol Consumption Affect Academic Performance?||00:00:00|
|5.4. Hypothesis Testing – Do Male Teenagers Drink More Than Females?||00:00:00|
|Section 6: Introduction to Predictive Analytics Models|
|6.1. Introduction to Predictive Analytics Models||00:00:00|
|6.2. The Scikit-Learn Library – Building a Simple Predictive Model||00:00:00|
|6.3. Classification – Predicting the Drinking Habits of Teenagers||00:00:00|
|6.4. Regression – Predicting House Prices||00:00:00|
|Mock Exam : Become a Python Data Analyst||00:40:00|
|Exam : Become a Python Data Analyst||00:40:00|